This GitHub repository contains an updated list of Federated Learning papers as of December 11, 2024.
- The resources are collected from various sources, including arXiv, NeurIPS, ICML, ICLR, ACL, EMNLP, AAAI, IJCAI, KDD, CVPR, ICCV, ECCV, NIPS, IEEE, ACM, Springer, ScienceDirect, Wiley, Nature, Science, and other top AI/ML conferences and journals.
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Explore additional research papers on the following topics:
- For Large Language Models papers, please visit the LLM Repository.
- For Backdoor Learning papers, please visit the Backdoor Learning Repository.
- For Federated Learning papers, please visit the Federated Learning Repository.
- For Machine Unlearning papers, please visit the Machine Unlearning Repository.
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Due to GitHub repository limitations, this section includes only those papers that provide accompanying code, sorted by publish date. For access to the full list of papers, please visit the Shinyapps website.
| No. | Title | Authors | Publish Date | Venue | Code | URL |
|---|---|---|---|---|---|---|
| 1 | DapperFL: Domain Adaptive Federated Learning with Model Fusion Pruning for Edge Devices | Yongzhe Jia, Xuyun Zhang, Hongsheng Hu, Kim-Kwang Raymond Choo, Lianyong Qi, Xiaolong Xu, Amin Beheshti, Wanchun Dou | 2024-12-08 | arXiv | https://github.com/jyzgh/DapperFL | http://arxiv.org/abs/2412.05823v1 |
| 2 | One-shot Federated Learning via Synthetic Distiller-Distillate Communication | Junyuan Zhang, Songhua Liu, Xinchao Wang | 2024-12-06 | arXiv | https://github.com/Carkham/FedSD2C | http://arxiv.org/abs/2412.05186v1 |
| 3 | BEFL: Balancing Energy Consumption in Federated Learning for Mobile Edge IoT | Zehao Ju, Tongquan Wei, Fuke Shen | 2024-12-06 | arXiv:2412.03950, 2024 | https://github.com/juzehao/BEFL | http://arxiv.org/abs/2412.03950v1 |
| 4 | FedDW: Distilling Weights through Consistency Optimization in Heterogeneous Federated Learning | Jiayu Liu, Yong Wang, Nianbin Wang, Jing Yang, Xiaohui Tao | 2024-12-05 | arXiv | https://github.com/liuvvvvv1/FedDW | http://arxiv.org/abs/2412.04521v1 |
| 5 | FedAH: Aggregated Head for Personalized Federated Learning | Pengzhan Zhou, Yuepeng He, Yijun Zhai, Kaixin Gao, Chao Chen, Zhida Qin, Chong Zhang, Songtao Guo | 2024-12-04 | arXiv …, 2024 | https://github.com/heyuepeng/FedAH | http://arxiv.org/abs/2412.01295v1 |
| 6 | FedPAW: Federated Learning With Personalized Aggregation Weights for Urban Vehicle Speed Prediction | Yuepeng He, Pengzhan Zhou, Yijun Zhai, Fang Qu, Zhida Qin, Mingyan Li, Songtao Guo | 2024-12-02 | IEEE Transactions on Cloud Computing | https://github.com/heyuepeng/PFLlibVSP | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10663571 |
| 7 | Distributed Backdoor Attacks on Federated Graph Learning and Certified Defenses | Yuxin Yang, Qiang Li, Jinyuan Jia, Yuan Hong, Binghui Wang | 2024-12 | CCS '24: Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security | https://github.com/Yuxin104/Opt-GDBA | https://dl.acm.org/doi/10.1145/3658644.3690187 |
| 8 | Federated Continual Graph Learning | Yinlin Zhu, Xunkai Li, Miao Hu, Di Wu | 2024-11-28 | arXiv | https://github.com/zyl24/FCGL_POWER | http://arxiv.org/abs/2411.18919v1 |
| 9 | Personalized Federated Fine-Tuning for LLMs via Data-Driven Heterogeneous Model Architectures | Yicheng Zhang, Zhen Qin, Zhaomin Wu, Shuiguang Deng | 2024-11-28 | arXiv | https://github.com/zyc140345/FedAMoLE | http://arxiv.org/abs/2411.19128v1 |
| 10 | Adaptive client selection with personalization for communication efficient Federated Learning | Allan Mariano de Souza, Filipe Maciel, Joahannes B. D. da Costa, Luiz F. Bittencourt, Eduardo Cerqueira, Antonio A. F. Loureiro, Leandro A. Villas | 2024-11-26 | Ad Hoc Networks | https://github.com/AllanMSouza/ACSP-FL | https://doi.org/10.1016/j.adhoc.2024.103462 |
| 11 | Energy-efficient Federated Learning with Dynamic Model Size Allocation | M S Chaitanya Kumar, Sai Satya Narayana J, Yunkai Bao, Xin Wang, Steve Drew | 2024-11-24 | arXiv:2411.15481, 2024 | https://github.com/denoslab/CAMA | http://arxiv.org/abs/2411.15481v1 |
| 12 | FedMLLM: Federated Fine-tuning MLLM on Multimodal Heterogeneity Data | Binqian Xu, Xiangbo Shu, Haiyang Mei, Guosen Xie, Basura Fernando, Mike Zheng Shou, Jinhui Tang | 2024-11-23 | arXiv …, 2024 | https://github.com/1xbq1/FedMLLM | http://arxiv.org/abs/2411.14717v1 |
| 13 | FedRAV: Hierarchically Federated Region-Learning for Traffic Object Classification of Autonomous Vehicles | Yijun Zhai, Pengzhan Zhou, Yuepeng He, Fang Qu, Zhida Qin, Xianlong Jiao, Guiyan Liu, Songtao Guo | 2024-11-22 | arXiv …, 2024 | https://github.com/yjzhai-cs/FedRAV | http://arxiv.org/abs/2411.13979v1 |
| 14 | Freezing of Gait Detection Using Gramian Angular Fields and Federated Learning from Wearable Sensors | Shovito Barua Soumma, S M Raihanul Alam, Rudmila Rahman, Umme Niraj Mahi, Abdullah Mamun, Sayyed Mostafa Mostafavi, Hassan Ghasemzadeh | 2024-11-21 | arXiv e …, 2024 | https://github.com/shovito66/FOGSense | http://arxiv.org/abs/2411.11764v2 |
| 15 | Federated Learning Client Pruning for Noisy Labels | Mahdi Morafah, Hojin Chang, Chen Chen, Bill Lin | 2024-11-11 | ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS), Just Accepted | https://github.com/MMorafah/ClipFL | https://dl.acm.org/doi/10.1145/3706058 |
| 16 | Masked Autoencoders are Efficient Continual Federated Learners | Subarnaduti Paul, Lars-Joel Frey, Roshni Kamath, Kristian Kersting, Martin Mundt | 2024-11-06 | arXiv:2411.01916, 2024 | https://github.com/ycheoo/pMAE | http://arxiv.org/abs/2306.03542v1 |
| 17 | FPPL: An Efficient and Non-IID Robust Federated Continual Learning Framework | Yuchen He, Chuyun Shen, Xiangfeng Wang, Bo Jin | 2024-11-05 | arXiv:2411.01904, 2024 | https://github.com/ycheoo/FPPL | http://arxiv.org/abs/2411.01904v1 |
| 18 | Identify Backdoored Model in Federated Learning via Individual Unlearning | Jiahao Xu, Zikai Zhang, Rui Hu | 2024-11-02 | arXiv:2411.01040, 2024 | https://github.com/JiiahaoXU/MASA | http://arxiv.org/abs/2411.01040v1 |
| 19 | Local Superior Soups: A Catalyst for Model Merging in Cross-Silo Federated Learning | Minghui Chen, Meirui Jiang, Xin Zhang, Qi Dou, Zehua Wang, Xiaoxiao Li | 2024-11-01 | arXiv | https://github.com/ubc-tea/Local-Superior-Soups | https://doi.org/10.48550/arXiv.2410.23660 |
| 20 | Federated Black-Box Adaptation for Semantic Segmentation | Jay N. Paranjape, Shameema Sikder, S. Swaroop Vedula, Vishal M. Patel | 2024-11-01 | arXiv …, 2024 | https://github.com/JayParanjape/blackfed/tree/master | http://arxiv.org/abs/2410.24181v1 |
| 21 | FedCVD: The First Real-World Federated Learning Benchmark on Cardiovascular Disease Data | Yukun Zhang, Guanzhong Chen, Zenglin Xu, Jianyong Wang, Dun Zeng, Junfan Li, Jinghua Wang, Yuan Qi, Irwin King | 2024-10-28 | arXiv | https://github.com/SMILELab-FL/FedCVD | http://arxiv.org/abs/2411.07050v1 |
| 22 | FedSSP: Federated Graph Learning with Spectral Knowledge and Personalized Preference | Zihan Tan, Guancheng Wan, Wenke Huang, Mang Ye | 2024-10-26 | arXiv | https://github.com/OakleyTan/FedSSP | https://doi.org/10.48550/arXiv.2410.20105 |
| 23 | Classifier Clustering and Feature Alignment for Federated Learning under Distributed Concept Drift | Junbao Chen, Jingfeng Xue, Yong Wang, Zhenyan Liu, Lu Huang | 2024-10-25 | arXiv | https://github.com/Chen-Junbao/FedCCFA | https://doi.org/10.48550/arXiv.2410.18478 |
| 24 | FedGMark: Certifiably Robust Watermarking for Federated Graph Learning | Yuxin Yang, Qiang Li, Yuan Hong, Binghui Wang | 2024-10-24 | arXiv | https://github.com/Yuxin104/FedGMark | https://doi.org/10.48550/arXiv.2410.17533 |
| 25 | Evaluating Federated Kolmogorov-Arnold Networks on Non-IID Data | Arthur Mendonça Sasse, Claudio Miceli de Farias | 2024-10-19 | arXiv e-prints, 2024 | https://github.com/artsasse/fedkan | http://arxiv.org/abs/2410.08961v1 |
| 26 | FedCert: Federated Accuracy Certification | Minh Hieu Nguyen, Huu Tien Nguyen, Trung Thanh Nguyen, Manh Duong Nguyen, Trong Nghia Hoang, Truong Thao Nguyen, Phi Le Nguyen | 2024-10-19 | arXiv e …, 2024 | https://github.com/thanhhff/FedCert/ | http://arxiv.org/abs/2410.03067v1 |
| 27 | DEeR: Deviation Eliminating and Noise Regulating for Privacy-preserving Federated Low-rank Adaptation | Meilu Zhu, Axiu Mao, Jun Liu, Yixuan Yuan | 2024-10-16 | arXiv | https://github.com/CUHK-AIM-Group/DEeR | http://arxiv.org/abs/2410.12926v1 |
| 28 | Adversarially Guided Stateful Defense Against Backdoor Attacks in Federated Deep Learning | Hassan Ali, Surya Nepal, Salil S. Kanhere, Sanjay K. Jha | 2024-10-15 | arXiv | https://github.com/hassanalikhatim/AGSD | https://doi.org/10.48550/arXiv.2410.11205 |
| 29 | FedCCRL: Federated Domain Generalization with Cross-Client Representation Learning | Xinpeng Wang, Yongxin Guo, Xiaoying Tang | 2024-10-15 | arXiv | https://github.com/SanphouWang/FedCCRL | https://doi.org/10.48550/arXiv.2410.11267 |
| 30 | FOOGD: Federated Collaboration for Both Out-of-distribution Generalization and Detection | Xinting Liao, Weiming Liu, Pengyang Zhou, Fengyuan Yu, Jiahe Xu, Jun Wang, Wenjie Wang, Chaochao Chen, Xiaolin Zheng | 2024-10-15 | arXiv | https://github.com/XeniaLLL/FOOGD-main | http://arxiv.org/abs/2410.11397v1 |
| 31 | Bridging Gaps: Federated Multi-View Clustering in Heterogeneous Hybrid Views | Xinyue Chen, Yazhou Ren, Jie Xu, Fangfei Lin, Xiaorong Pu, Yang Yang | 2024-10-12 | arXiv | https://github.com/5Martina5/FMCSC | http://arxiv.org/abs/2410.09484v1 |
| 32 | Exact Aggregation for Federated and Efficient Fine-Tuning of Foundation Models | Raghav Singhal, Kaustubh Ponkshe, Praneeth Vepakomma | 2024-10-12 | arXiv | https://github.com/RaghavSinghal10/fedex-lora | http://arxiv.org/abs/2410.09432v1 |
| 33 | Benchmarking Data Heterogeneity Evaluation Approaches for Personalized Federated Learning | Zhilong Li, Xiaohu Wu, Xiaoli Tang, Tiantian He, Yew-Soon Ong, Mengmeng Chen, Qiqi Liu, Qicheng Lao, Xiaoxiao Li, Han Yu | 2024-10-09 | arXiv | https://github.com/Xiaoni-61/DH-Benchmark | https://doi.org/10.48550/arXiv.2410.07286 |
| 34 | FedGraph: A Research Library and Benchmark for Federated Graph Learning | Yuhang Yao, Yuan Li, Xinyi Fan, Junhao Li, Kay Liu, Weizhao Jin, Srivatsan Ravi, Philip S. Yu, Carlee Joe-Wong | 2024-10-08 | arXiv | https://github.com/FedGraph/fedgraph | https://doi.org/10.48550/arXiv.2410.06340 |
| 35 | FACMIC: Federated Adaptative CLIP Model for Medical Image Classification | Yihang Wu, Christian Desrosiers, Ahmad Chaddad | 2024-10-08 | GoogleScholar | https://github.com/AIPMLab/FACMIC | http://arxiv.org/abs/2410.14707v1 |
| 36 | Deep Domain Isolation and Sample Clustered Federated Learning for Semantic Segmentation | Matthis Manthe, Carole Lartizien, Stefan Duffner | 2024-10-04 | ECML/PKDD | https://github.com/MatthisManthe/DDI_SCFL | https://doi.org/10.1007/978-3-031-70359-1_22 |
| 37 | FedStein: Enhancing Multi-Domain Federated Learning Through James-Stein Estimator | Sunny Gupta, Nikita Jangid, Amit Sethi | 2024-10-04 | arXiv | https://github.com/sunnyinAI/FedStein | https://doi.org/10.48550/arXiv.2410.03499 |
| 38 | Selective Aggregation for Low-Rank Adaptation in Federated Learning | Pengxin Guo, Shuang Zeng, Yanran Wang, Huijie Fan, Feifei Wang, Liangqiong Qu | 2024-10-02 | arXiv | https://github.com/Pengxin-Guo/FedSA-LoRA | https://doi.org/10.48550/arXiv.2410.01463 |
| 39 | Demo: FedCampus: A Real-world Privacy-preserving Mobile Application for Smart Campus via Federated Learning & Analytics | Jiaxiang Geng, Beilong Tang, Boyan Zhang, Jiaqi Shao, Bing Luo | 2024-10 | MOBIHOC '24: Proceedings of the Twenty-fifth International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing | https://github.com/FedCampus/FedCampus_Flutter | https://dl.acm.org/doi/10.1145/3641512.3690630 |
| 40 | DualFed: Enjoying both Generalization and Personalization in Federated Learning via Hierachical Representations | Guogang Zhu, Xuefeng Liu, Jianwei Niu, Shaojie Tang, Xinghao Wu, Jiayuan Zhang | 2024-10 | MM '24: Proceedings of the 32nd ACM International Conference on Multimedia | https://github.com/GuogangZhu/DualFed | https://dl.acm.org/doi/10.1145/3664647.3681260 |
| 41 | PIP: Prototypes-Injected Prompt for Federated Class Incremental Learning | Muhammad Anwar Ma'sum, Mahardhika Pratama, Savitha Ramasamy, Lin Liu, Habibullah Habibullah, Ryszard Kowalczyk | 2024-10 | CIKM '24: Proceedings of the 33rd ACM International Conference on Information and Knowledge Management | https://github.com/anwarmaxsum/PIP | https://dl.acm.org/doi/10.1145/3627673.3679794 |
| 42 | Decoupling General and Personalized Knowledge in Federated Learning via Additive and Low-rank Decomposition | Xinghao Wu, Xuefeng Liu, Jianwei Niu, Haolin Wang, Shaojie Tang, Guogang Zhu, Hao Su | 2024-10 | MM '24: Proceedings of the 32nd ACM International Conference on Multimedia | https://github.com/XinghaoWu/FedDecomp | https://dl.acm.org/doi/10.1145/3664647.3681588 |
| 43 | Tackling Noisy Clients in Federated Learning with End-to-end Label Correction | Xuefeng Jiang, Sheng Sun, Jia Li, Jingjing Xue, Runhan Li, Zhiyuan Wu, Gang Xu, Yuwei Wang, Min Liu | 2024-10 | CIKM '24: Proceedings of the 33rd ACM International Conference on Information and Knowledge Management | https://github.com/Sprinter1999/FedELC | https://dl.acm.org/doi/10.1145/3627673.3679550 |
| 44 | Medical Federated Model with Mixture of Personalized and Shared Components | Yawei Zhao, Qinghe Liu, Xinwang Liu, Kunlun He | 2024-09-28 | IEEE Transactions on Pattern Analysis and Machine Intelligence | https://github.com/ | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10697408 |
| 45 | PILoRA: Prototype Guided Incremental LoRA for Federated Class-Incremental Learning | Haiyang Guo, Fei Zhu, Wenzhuo Liu, Xu-Yao Zhang, Cheng-Lin Liu | 2024-09-27 | ECCV | https://github.com/Ghy0501/PILoRA | https://doi.org/10.1007/978-3-031-73650-6_9 |
| 46 | Towards Diverse Device Heterogeneous Federated Learning via Task Arithmetic Knowledge Integration | Mahdi Morafah, Vyacheslav Kungurtsev, Hojin Chang, Chen Chen, Bill Lin | 2024-09-27 | arXiv | https://github.com/MMorafah/TAKFL | https://doi.org/10.48550/arXiv.2409.18461 |
| 47 | Hierarchical Federated Learning with Multi-Timescale Gradient Correction | Wenzhi Fang, Dong-Jun Han, Evan Chen, Shiqiang Wang, Christopher G. Brinton | 2024-09-27 | arXiv | https://github.com/wenzhifang/MTGC | https://doi.org/10.48550/arXiv.2409.18448 |
| 48 | Vehicle Selection for C-V2X Mode 4-Based Federated Edge Learning Systems | Qiong Wu, Xiaobo Wang, Pingyi Fan, Qiang Fan, Huiling Zhu, Jiangzhou Wang | 2024-09-27 | IEEE Systems Journal | https://github.com/qiongwu86/Vehicle-selection-for-C-V2X | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10695132 |
| 49 | FedSlate:A Federated Deep Reinforcement Learning Recommender System | Yongxin Deng, Xiaoyu Tan, Xihe Qiu, Yaochu Jin | 2024-09-24 | arXiv | https://github.com/TianYaDY/FedSlate | https://doi.org/10.48550/arXiv.2409.14872 |
| 50 | FLeNS: Federated Learning with Enhanced Nesterov-Newton Sketch | Sunny Gupta, Mohit Jindal, Pankhi Kashyap, Pranav Jeevan, Amit Sethi | 2024-09-24 | arXiv | https://github.com/sunnyinAI/FLeNS | https://doi.org/10.48550/arXiv.2409.15216 |
| 51 | FEDL: Confidential Deep Learning for Autonomous Driving in VANETs Based on Functional Encryption | M. Tang, Z. Huang, G. Deng | 2024-09-24 | IEEE Transactions on Intelligent Transportation Systems | https://github.com/HuangZengyi/FEDL | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10689332 |
| 52 | Federated Learning with Label-Masking Distillation | Jianghu Lu, Shikun Li, Kexin Bao, Pengju Wang, Zhenxing Qian, Shiming Ge | 2024-09-20 | MM '23: Proceedings of the 31st ACM International Conference on Multimedia | https://github.com/wnma3mz/FedLMD | https://dl.acm.org/doi/10.1145/3581783.3611984 |
| 53 | FedLF: Adaptive Logit Adjustment and Feature Optimization in Federated Long-Tailed Learning | Xiuhua Lu, Peng Li, Xuefeng Jiang | 2024-09-19 | arXiv | https://github.com/18sym/FedLF | https://doi.org/10.48550/arXiv.2409.12105 |
| 54 | Advances in APPFL: A Comprehensive and Extensible Federated Learning Framework | Zilinghan Li, Shilan He, Ze Yang, Minseok Ryu, Kibaek Kim, Ravi K. Madduri | 2024-09-17 | arXiv | https://github.com/APPFL/APPFL | https://doi.org/10.48550/arXiv.2409.11585 |
| 55 | AdaFedProx: A Heterogeneity-Aware Federated Deep Reinforcement Learning for Medical Image Classification | P. Sahoo, A. Tripathi, S. Saha, S. Mondal, J. P. Singh, B. Sharma | 2024-09-16 | IEEE Transactions on Consumer Electronics | https://github.com/Pranabiitp/AdaFedProx | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10681112 |
| 56 | Federated Feature Augmentation and Alignment | T. Zhou, Y. Yuan, B. Wang, E. Konukoglu | 2024-09-16 | IEEE Transactions on Pattern Analysis and Machine Intelligence | https://github.com/tfzhou/FedFA | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10680999 |
| 57 | A Unified Framework for Federated Semi-Supervised Learning in Heterogeneous IoT Healthcare Systems | B. Li, W. Gao, J. Xie, H. Li, M. Gong | 2024-09-11 | IEEE Internet of Things Journal | https://github.com/baoshengli96/FSSL-HD | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10673976 |
| 58 | FLoRA: Federated Fine-Tuning Large Language Models with Heterogeneous Low-Rank Adaptations | Ziyao Wang, Zheyu Shen, Yexiao He, Guoheng Sun, Hongyi Wang, Lingjuan Lyu, Ang Li | 2024-09-10 | OpenReview | https://github.com/ATP-1010/FederatedLLM | http://arxiv.org/abs/2409.05976v1 |
| 59 | Buffer-based Gradient Projection for Continual Federated Learning | Shenghong Dai, Jy-yong Sohn, Yicong Chen, S. M. Iftekharul Alam, Ravikumar Balakrishnan, Suman Banerjee, Nageen Himayat, Kangwook Lee | 2024-09-04 | arXiv | https://github.com/shenghongdai/Fed-A-GEM | https://doi.org/10.48550/arXiv.2409.01585 |
| 60 | Diffusion-Driven Data Replay: A Novel Approach to Combat Forgetting in Federated Class Continual Learning | Jinglin Liang, Jin Zhong, Hanlin Gu, Zhongqi Lu, Xingxing Tang, Gang Dai, Shuangping Huang, Lixin Fan, Qiang Yang | 2024-09-02 | arXiv | https://github.com/jinglin-liang/DDDR | https://doi.org/10.48550/arXiv.2409.01128 |
| 61 | Fed-MUnet: Multi-modal Federated Unet for Brain Tumor Segmentation | Ruojun Zhou, Lisha Qu, Lei Zhang, Ziming Li, Hongwei Yu, Bing Luo | 2024-09-02 | arXiv | https://github.com/Arnold-Jun/Fed-MUnet | http://arxiv.org/abs/2409.01020v1 |
| 62 | Achieving Byzantine-Resilient Federated Learning via Layer-Adaptive Sparsified Model Aggregation | Jiahao Xu, Zikai Zhang, Rui Hu | 2024-09-02 | arXiv | https://github.com/JiiahaoXU/LASA | https://doi.org/10.48550/arXiv.2409.01435 |
| 63 | Model-based federated learning for accurate MR image reconstruction from undersampled k-space data | Ruoyou Wu, Cheng Li, Juan Zou, Qiegen Liu, Hairong Zheng, Shanshan Wang | 2024-09-01 | Comput. Biol. Medicine | https://github.com/ternencewu123/ModFed | https://doi.org/10.1016/j.compbiomed.2024.108905 |
| 64 | Federated Learning and Differential Privacy Techniques on Multi-hospital Population-scale Electrocardiogram Data | Vikhyat Agrawal, Sunil Vasu Kalmady, Venkataseetharam Manoj Malipeddi, Manisimha Varma Manthena, Weijie Sun, Saiful Islam, Abram Hindle, Padma Kaul, Russell Greiner | 2024-09 | ICMHI '24: Proceedings of the 2024 8th International Conference on Medical and Health Informatics | https://github.com/vikhyatt/Hospital-FL-DP | https://dl.acm.org/doi/10.1145/3673971.3673990 |
| 65 | VFLIP: A Backdoor Defense for Vertical Federated Learning via Identification and Purification | Yungi Cho, Woorim Han, Miseon Yu, Younghan Lee, Ho Bae, Yunheung Paek | 2024-08-29 | ESORICS | https://github.com/blingcho/VFLIP-esorics24 | https://doi.org/10.1007/978-3-031-70903-6_15 |
| 66 | DRL-Based Federated Self-Supervised Learning for Task Offloading and Resource Allocation in ISAC-Enabled Vehicle Edge Computing | Xueying Gu, Qiong Wu, Pingyi Fan, Nan Cheng, Wen Chen, Khaled B. Letaief | 2024-08-28 | arXiv | https://github.com/qiongwu86/Federated-SSL-task-offloading-and-resource-allocation | https://doi.org/10.48550/arXiv.2408.14831 |
| 67 | Federated User Preference Modeling for Privacy-Preserving Cross-Domain Recommendation | Li Wang, Shoujin Wang, Quangui Zhang, Qiang Wu, Min Xu | 2024-08-27 | arXiv:2408.14689, 2024 | https://github.com/Lili1013/FUPM | http://arxiv.org/abs/2408.14689v1 |
| 68 | FederatedScope-LLM: A Comprehensive Package for Fine-tuning Large Language Models in Federated Learning | Weirui Kuang, Bingchen Qian, Zitao Li, Daoyuan Chen, Dawei Gao, Xuchen Pan, Yuexiang Xie, Yaliang Li, Bolin Ding, Jingren Zhou | 2024-08-25 | KDD '24: Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining | https://github.com/alibaba/FederatedScope/tree/llm | https://dl.acm.org/doi/10.1145/3637528.3671573 |
| 69 | Personalized Federated Continual Learning via Multi-Granularity Prompt | Hao Yu, Xin Yang, Xin Gao, Yan Kang, Hao Wang, Junbo Zhang, Tianrui Li | 2024-08-25 | KDD '24: Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining | https://github.com/SkyOfBeginning/FedMGP | https://dl.acm.org/doi/10.1145/3637528.3671948 |
| 70 | OpenFedLLM: Training Large Language Models on Decentralized Private Data via Federated Learning | Rui Ye, Wenhao Wang, Jingyi Chai, Dihan Li, Zexi Li, Yinda Xu, Yaxin Du, Yanfeng Wang, Siheng Chen | 2024-08-25 | KDD '24: Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining | https://github.com/rui-ye/OpenFedLLM | https://dl.acm.org/doi/10.1145/3637528.3671582 |
| 71 | FLea: Addressing Data Scarcity and Label Skew in Federated Learning via Privacy-preserving Feature Augmentation | Tong Xia, Abhirup Ghosh, Xinchi Qiu, Cecilia Mascolo | 2024-08-25 | KDD '24: Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining | https://github.com/XTxiatong/FLea | https://dl.acm.org/doi/10.1145/3637528.3671899 |
| 72 | Federated Graph Learning with Structure Proxy Alignment | Xingbo Fu, Zihan Chen, Binchi Zhang, Chen Chen, Jundong Li | 2024-08-25 | KDD '24: Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining | https://github.com/xbfu/FedSpray | https://dl.acm.org/doi/10.1145/3637528.3671717 |
| 73 | FedSAC: Dynamic Submodel Allocation for Collaborative Fairness in Federated Learning | Zihui Wang, Zheng Wang, Lingjuan Lyu, Zhaopeng Peng, Zhicheng Yang, Chenglu Wen, Rongshan Yu, Cheng Wang, Xiaoliang Fan | 2024-08-25 | KDD '24: Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining | https://github.com/wangzihuixmu/FedSAC | https://dl.acm.org/doi/10.1145/3637528.3671748 |
| 74 | Tackling Data Heterogeneity in Federated Learning via Loss Decomposition | Shuang Zeng, Pengxin Guo, Shuai Wang, Jianbo Wang, Yuyin Zhou, Liangqiong Qu | 2024-08-23 | arXiv | https://github.com/Zeng-Shuang/FedLD | https://doi.org/10.48550/arXiv.2408.12300 |
| 75 | FedGS: Federated Gradient Scaling for Heterogeneous Medical Image Segmentation | Philip Schutte, Valentina Corbetta, Regina Beets-Tan, Wilson Silva | 2024-08-22 | arXiv …, 2024 | https://github.com/Trustworthy-AI-UU-NKI/Federated-Learning-Disentanglement | http://arxiv.org/abs/2408.11701v1 |
| 76 | DRL-Based Resource Allocation for Motion Blur Resistant Federated Self-Supervised Learning in IoV | Xueying Gu, Qiong Wu, Pingyi Fan, Qiang Fan, Nan Cheng, Wen Chen, Khaled B. Letaief | 2024-08-17 | arXiv | https://github.com/qiongwu86/DRL-BFSSL | https://doi.org/10.48550/arXiv.2408.09194 |
| 77 | Federated Fairness Analytics: Quantifying Fairness in Federated Learning | Oscar Dilley, Juan Marcelo Parra Ullauri, Rasheed Hussain, Dimitra Simeonidou | 2024-08-16 | arXiv | https://github.com/oscardilley/federated-fairness | https://doi.org/10.48550/arXiv.2408.08214 |
| 78 | Centralized and Federated Heart Disease Classification Models Using UCI Dataset and their Shapley-value Based Interpretability | Mario Padilla Rodriguez, Mohamed Nafea | 2024-08-15 | arXiv e-prints, 2024 | https://github.com/padillma1/Heart-Disease-Classification-on-UCI-dataset-and-Shapley-Interpretability-Analysis | http://arxiv.org/abs/2408.06183v2 |
| 79 | A Comprehensive Federated Learning Framework for Diabetic Retinopathy Grading and Lesion Segmentation | J. Mao, X. Ma, Y. Bi, R. Zhang | 2024-08-14 | IEEE Transactions on Big Data | https://github.com/NekoPii/TJDR-FL | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10634805 |
| 80 | Understanding Byzantine Robustness in Federated Learning with A Black-box Server | Fangyuan Zhao, Yuexiang Xie, Xuebin Ren, Bolin Ding, Shusen Yang, Yaliang Li | 2024-08-12 | arXiv | https://github.com/alibaba/FederatedScope/tree/Byzantine_attack_defense | https://doi.org/10.48550/arXiv.2408.06042 |
| 81 | Personalizing Federated Instrument Segmentation with Visual Trait Priors in Robotic Surgery | Jialang Xu, Jiacheng Wang, Lequan Yu, Danail Stoyanov, Yueming Jin, Evangelos B. Mazomenos | 2024-08-06 | arXiv | https://github.com/wzjialang/PFedSIS | http://arxiv.org/abs/2408.03208v1 |
| 82 | Mobility-Aware Federated Self-supervised Learning in Vehicular Network | Xueying Gu, Qiong Wu, Pingyi Fan, Qiang Fan | 2024-08-02 | arXiv | https://github.com/qiongwu86/FLSimCo | https://doi.org/10.48550/arXiv.2408.00256 |
| 83 | FedBChain: A Blockchain-enabled Federated Learning Framework for Improving DeepConvLSTM with Comparative Strategy Insights | Gaoxuan Li, Chern Hong Lim, Qiyao Ma, Xinyu Tang, Hwa Hui Tew, Fan Ding, Xuewen Luo | 2024-08-01 | arXiv | https://github.com/Glen909/FedBChain | https://doi.org/10.48550/arXiv.2407.21282 |
| 84 | F-KANs: Federated Kolmogorov-Arnold Networks | Engin Zeydan, Cristian J. Vaca-Rubio, Luis Blanco, Roberto Pereira, Marius Caus, Abdullah Aydeger | 2024-07-30 | arXiv …, 2024 | https://github.com/ezeydan/F-KANs | http://arxiv.org/abs/2407.20100v2 |
| 85 | Multi-level Collaborative Learning for Multi-Target Domain Adaptive Semantic Segmentation | F. Ding, J. Li | 2024-07-30 | IEEE Transactions on Circuits and Systems for Video Technology | https://github.com/feifei-cv/MCL | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10614657 |
| 86 | UniFed: A Universal Federation of a Mixture of Highly Heterogeneous Medical Image Classification Tasks | Atefe Hassani, Islem Rekik | 2024-07-29 | arXiv | https://github.com/basiralab/UniFed | http://arxiv.org/abs/2408.07075v2 |
| 87 | Joint Optimization of Fairness and Energy Efficiency in Zero-Trust Federated Learning for Consumer Internet of Things: A Lossy Communication Perspective | K. Zhang, J. Sun, Q. Feng, X. Huang, C. Jiang, M. S. Hossain | 2024-07-29 | IEEE Transactions on Consumer Electronics | https://github.com/sunjia123456789/The-Faired-FL | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10612832 |
| 88 | HF-Fed: Hierarchical based customized Federated Learning Framework for X-Ray Imaging | Tajamul Ashraf, Tisha Madame | 2024-07-26 | arXiv | https://tisharepo.github.io/Webpage/ | https://doi.org/10.48550/arXiv.2407.17780 |
| 89 | COALA: A Practical and Vision-Centric Federated Learning Platform | Weiming Zhuang, Jian Xu, Chen Chen, Jingtao Li, Lingjuan Lyu | 2024-07-23 | arXiv | https://github.com/SonyResearch/COALA | https://doi.org/10.48550/arXiv.2407.16560 |
| 90 | Generalizable Reconstruction for Accelerating MR Imaging via Federated Learning with Neural Architecture Search | R. Wu, C. Li, J. Zou, X. Liu, H. Zheng, S. Wang | 2024-07-23 | IEEE Transactions on Medical Imaging | https://github.com/ternencewu123/GAutoMRI | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10606250 |
| 91 | A Learning-Based Attack Framework to Break SOTA Poisoning Defenses in Federated Learning | Yuxin Yang, Qiang Li, Chenfei Nie, Yuan Hong, Meng Pang, Binghui Wang | 2024-07-21 | arXiv | https://github.com/Yuxin104/ | https://doi.org/10.48550/arXiv.2407.15267 |
| 92 | Learning Unlabeled Clients Divergence via Anchor Model Aggregation for Federated Semi-supervised Learning | Marawan Elbatel, Hualiang Wang, Jixiang Chen, Hao Wang, Xiaomeng Li | 2024-07-14 | arXiv | https://github.com/xmed-lab/SemiAnAgg | https://doi.org/10.48550/arXiv.2407.10327 |
| 93 | CAR-MFL: Cross-Modal Augmentation by Retrieval for Multimodal Federated Learning with Missing Modalities | Pranav Poudel, Prashant Shrestha, Sanskar Amgain, Yash Raj Shrestha, Prashnna K. Gyawali, Binod Bhattarai | 2024-07-12 | arXiv | https://github.com/bhattarailab/CAR-MFL | https://doi.org/10.48550/arXiv.2407.08648 |
| 94 | Distributed Deep Reinforcement Learning Based Gradient Quantization for Federated Learning Enabled Vehicle Edge Computing | Cui Zhang, Wenjun Zhang, Qiong Wu, Pingyi Fan, Qiang Fan, Jiangzhou Wang, Khaled B. Letaief | 2024-07-12 | IEEE Internet of Things Journal | https://github.com/qiongwu86/Distributed-Deep-Reinforcement-Learning-Based-Gradient | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10643168 |
| 95 | FUNAvg: Federated Uncertainty Weighted Averaging for Datasets with Diverse Labels | Malte Tölle, Fernando Navarro, Sebastian Eble, Ivo Wolf, Bjoern Menze, Sandy Engelhardt | 2024-07-12 | arXiv …, 2024 | https://github.com/Cardio-AI/FUNAvg | http://arxiv.org/abs/2407.07488v1 |
| 96 | FedMedICL: Towards Holistic Evaluation of Distribution Shifts in Federated Medical Imaging | Kumail Alhamoud, Yasir Ghunaim, Motasem Alfarra, Thomas Hartvigsen, Philip Torr, Bernard Ghanem, Adel Bibi, Marzyeh Ghassemi | 2024-07-11 | arXiv …, 2024 | https://github.com/m1k2zoo/FedMedICL | http://arxiv.org/abs/2407.08822v1 |
| 97 | FedMRL: Data Heterogeneity Aware Federated Multi-agent Deep Reinforcement Learning for Medical Imaging | Pranab Sahoo, Ashutosh Tripathi, Sriparna Saha, Samrat Mondal | 2024-07-10 | arXiv | https://github.com/Pranabiitp/FedMRL | https://doi.org/10.48550/arXiv.2407.05800 |
| 98 | Venomancer: Towards Imperceptible and Target-on-Demand Backdoor Attacks in Federated Learning | Son Nguyen, Thinh Nguyen, Khoa D. Doan, Kok-Seng Wong | 2024-07-04 | arXiv | https://github.com/nguyenhongson1902/Venomancer | https://doi.org/10.48550/arXiv.2407.03144 |
| 99 | Enable the Right to be Forgotten with Federated Client Unlearning in Medical Imaging | Zhipeng Deng, Luyang Luo, Hao Chen | 2024-07-02 | arXiv:2407.02356, 2024 | https://github.com/dzp2095/FCU | http://arxiv.org/abs/2407.02356v1 |
| 100 | FedIA: Federated Medical Image Segmentation with Heterogeneous Annotation Completeness | Yangyang Xiang, Nannan Wu, Li Yu, Xin Yang, Kwang-Ting Cheng, Zengqiang Yan | 2024-07-02 | arXiv …, 2024 | https://github.com/HUSTxyy/FedIA | http://arxiv.org/abs/2407.02280v2 |
| 101 | Optimizing Age of Information in Vehicular Edge Computing with Federated Graph Neural Network Multi-Agent Reinforcement Learning | Wenhua Wang, Qiong Wu, Pingyi Fan, Nan Cheng, Wen Chen, Jiangzhou Wang, Khaled B. Letaief | 2024-07-01 | arXiv | https://github.com/qiongwu86/Optimizing-AoI-in-VEC-with-Federated-Graph-Neural-Network-Multi-Agent-Reinforcement-Learning | https://doi.org/10.48550/arXiv.2407.02342 |
| 102 | A Whole-Process Certifiably Robust Aggregation Method Against Backdoor Attacks in Federated Learning | Anqi Zhou, Yezheng Liu, Yidong Chai, Hongyi Zhu, Xinyue Ge, Yuanchun Jiang, Meng Wang | 2024-06-30 | arXiv | https://github.com/brick-brick/WPCRAM | https://doi.org/10.48550/arXiv.2407.00719 |
| 103 | FedMLP: Federated Multi-Label Medical Image Classification under Task Heterogeneity | Zhaobin Sun, Nannan Wu, Junjie Shi, Li Yu, Xin Yang, Kwang-Ting Cheng, Zengqiang Yan | 2024-06-28 | arXiv …, 2024 | https://github.com/szbonaldo/FedMLP | http://arxiv.org/abs/2406.18995v1 |
| 104 | Contrastive Multi-bit Collaborative Learning for Deep Cross-modal Hashing | Q. Wu, Z. Zhang, Y. Liu, J. Zhang, L. Nie | 2024-06-26 | IEEE Transactions on Knowledge and Data Engineering | https://github.com/sky-wz/CMCL | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10572365 |
| 105 | Quantum Fuzzy Federated Learning for Privacy Protection in Intelligent Information Processing | Z. Qu, L. Zhang, P. Tiwari | 2024-06-26 | IEEE Transactions on Fuzzy Systems | https://github.com/LASTsue/QFFL | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10572363 |
| 106 | Heterogeneous Federated Domain Generalization Network With Common Representation Learning for Cross-Load Machinery Fault Diagnosis | Quan Qian, Jun Luo, Yi Qin | 2024-06-25 | IEEE Transactions on Systems, Man, and Cybernetics: Systems | https://qinyi-team.github.io/2024/05/Heterogeneous-federated-domain-generalization-network | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10571357 |
| 107 | Low-Resource Machine Translation through the Lens of Personalized Federated Learning | Viktor Moskvoretskii, Nazarii Tupitsa, Chris Biemann, Samuel Horváth, Eduard Gorbunov, Irina Nikishina | 2024-06-19 | arXiv | https://github.com/VityaVitalich/MeritFed | https://doi.org/10.48550/arXiv.2406.12564 |
| 108 | Federated Face Forgery Detection Learning with Personalized Representation | Decheng Liu, Zhan Dang, Chunlei Peng, Nannan Wang, Ruimin Hu, Xinbo Gao | 2024-06-18 | arXiv | https://github.com/GANG370/PFR-Forgery | https://doi.org/10.48550/arXiv.2406.11145 |
| 109 | Synergizing Foundation Models and Federated Learning: A Survey | Shenghui Li, Fanghua Ye, Meng Fang, Jiaxu Zhao, Yun-Hin Chan, Edith C. -H. Ngai, Thiemo Voigt | 2024-06-18 | arXiv | https://github.com/lishenghui/awesome-fm-fl | https://doi.org/10.48550/arXiv.2406.12844 |
| 110 | Feasibility of Federated Learning from Client Databases with Different Brain Diseases and MRI Modalities | Felix Wagner, Wentian Xu, Pramit Saha, Ziyun Liang, Daniel Whitehouse, David Menon, Virginia Newcombe, Natalie Voets, J. Alison Noble, Konstantinos Kamnitsas | 2024-06-17 | arXiv | https://github.com/FelixWag/FL-MultiDisease-MRI | https://doi.org/10.48550/arXiv.2406.11636 |
| 111 | Accelerating Communication-efficient Federated Multi-Task Learning With Personalization and Fairness | Renyou Xie, Chaojie Li, Xiaojun Zhou, Zhaoyang Dong | 2024-06-12 | IEEE Transactions on Parallel and Distributed Systems | https://github.com/xry21xdj/FedMGDA-M | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10552428 |
| 112 | FedLLM-Bench: Realistic Benchmarks for Federated Learning of Large Language Models | Rui Ye, Rui Ge, Xinyu Zhu, Jingyi Chai, Yaxin Du, Yang Liu, Yanfeng Wang, Siheng Chen | 2024-06-12 | arXiv | https://github.com/rui-ye/FedLLM-Bench | https://doi.org/10.48550/arXiv.2406.04845 |
| 113 | Fedhca2: Towards Hetero-Client Federated Multi-Task Learning | Yuxiang Lu, Suizhi Huang, Yuwen Yang, Shalayiding Sirejiding, Yue Ding, Hongtao Lu | 2024-06-12 | 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | https://github.com/innovator-zero/FedHCA2 | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10658480 |
| 114 | Privacy-Preserving Collaboration for Multi-Organ Segmentation via Federated Learning from Sites with Partial Labels | Adway U. Kanhere, Pranav Kulkarni, Paul H. Yi, Vishwa S. Parekh | 2024-06-12 | 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) | https://github.com/UM2ii/SegViz | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10678090 |
| 115 | Beyond Similarity: Personalized Federated Recommendation with Composite Aggregation | Honglei Zhang, Haoxuan Li, Jundong Chen, Sen Cui, Kunda Yan, Abudukelimu Wuerkaixi, Xin Zhou, Zhiqi Shen, Yidong Li | 2024-06-07 | arXiv …, 2024 | https://github.com/hongleizhang/FedCA | http://arxiv.org/abs/2406.03933v1 |
| 116 | FedPylot: Navigating Federated Learning for Real-Time Object Detection in Internet of Vehicles | Cyprien Quéméneur, Soumaya Cherkaoui | 2024-06-06 | arXiv | https://github.com/cyprienquemeneur/fedpylot | https://doi.org/10.48550/arXiv.2406.03611 |
| 117 | Accelerating Heterogeneous Federated Learning with Closed-form Classifiers | Eros Fanì, Raffaello Camoriano, Barbara Caputo, Marco Ciccone | 2024-06-04 | arXiv | https://fed-3r.github.io/ | https://doi.org/10.48550/arXiv.2406.01116 |
| 118 | A Novel Defense Against Poisoning Attacks on Federated Learning: LayerCAM Augmented with Autoencoder | Jingjing Zheng, Xin Yuan, Kai Li, Wei Ni, Eduardo Tovar, Jon Crowcroft | 2024-06-03 | arXiv | https://github.com/jjzgeeks/LayerCAM-AE | https://doi.org/10.48550/arXiv.2406.02605 |
| 119 | Redefining Contributions: Shapley-Driven Federated Learning | Nurbek Tastan, Samar Fares, Toluwani Aremu, Samuel Horváth, Karthik Nandakumar | 2024-06-02 | arXiv | https://github.com/tnurbek/shapfed | https://doi.org/10.48550/arXiv.2406.00569 |
| 120 | Pursuing Overall Welfare in Federated Learning through Sequential Decision Making | Seok-Ju Hahn, Gi-Soo Kim, Junghye Lee | 2024-06-01 | arXiv | https://github.com/vaseline555/AAggFF | https://doi.org/10.48550/arXiv.2405.20821 |
| 121 | Federated Multi-Task Learning on Non-IID Data Silos: An Experimental Study | Yuwen Yang, Yuxiang Lu, Suizhi Huang, Shalayiding Sirejiding, Hongtao Lu, Yue Ding | 2024-06 | ICMR '24: Proceedings of the 2024 International Conference on Multimedia Retrieval | https://github.com/youngfish42/FMTL-Benchmark | https://dl.acm.org/doi/10.1145/3652583.3657999 |
| 122 | Share Your Secrets for Privacy! Confidential Forecasting with Vertical Federated Learning | Aditya Shankar, Lydia Y. Chen, Jérémie Decouchant, Dimitra Gkorou, Rihan Hai | 2024-05-31 | arXiv | https://github.com/adis98/STV | https://doi.org/10.48550/arXiv.2405.20761 |
| 123 | Estimating before Debiasing: A Bayesian Approach to Detaching Prior Bias in Federated Semi-Supervised Learning | Guogang Zhu, Xuefeng Liu, Xinghao Wu, Shaojie Tang, Chao Tang, Jianwei Niu, Hao Su | 2024-05-30 | arXiv | https://github.com/GuogangZhu/FedDB | https://doi.org/10.48550/arXiv.2405.19789 |
| 124 | Fast-FedUL: A Training-Free Federated Unlearning with Provable Skew Resilience | Thanh Trung Huynh, Trong Bang Nguyen, Phi Le Nguyen, Thanh Tam Nguyen, Matthias Weidlich, Quoc Viet Hung Nguyen, Karl Aberer | 2024-05-30 | arXiv …, 2024 | https://github.com/thanhtrunghuynh93/fastFedUL | http://arxiv.org/abs/2405.18040v1 |
| 125 | Federated Learning under Partially Class-Disjoint Data via Manifold Reshaping | Ziqing Fan, Jiangchao Yao, Ruipeng Zhang, Lingjuan Lyu, Ya Zhang, Yanfeng Wang | 2024-05-30 | arXiv | https://github.com/MediaBrain-SJTU/FedMR | https://doi.org/10.48550/arXiv.2405.18983 |
| 126 | Federated Learning with Bilateral Curation for Partially Class-Disjoint Data | Ziqing Fan, Ruipeng Zhang, Jiangchao Yao, Bo Han, Ya Zhang, Yanfeng Wang | 2024-05-29 | NeurIPS | https://github.com/MediaBrain-SJTU/FedGELA | http://papers.nips.cc/paper_files/paper/2023/hash/65b721a1df04c1098567f70d483d6468-Abstract-Conference.html |
| 127 | Multi-Level Additive Modeling for Structured Non-IID Federated Learning | Shutong Chen, Tianyi Zhou, Guodong Long, Jie Ma, Jing Jiang, Chengqi Zhang | 2024-05-27 | arXiv | https://github.com/shutong043/FeMAM | https://doi.org/10.48550/arXiv.2405.16472 |
| 128 | Visualizing the Shadows: Unveiling Data Poisoning Behaviors in Federated Learning | Xueqing Zhang, Junkai Zhang, Ka-Ho Chow, Juntao Chen, Ying Mao, Mohamed Rahouti, Xiang Li, Yuchen Liu, Wenqi Wei | 2024-05-27 | arXiv | https://github.com/CathyXueqingZhang/DataPoisoningVis | https://doi.org/10.48550/arXiv.2405.16707 |
| 129 | Analytic Federated Learning | Huiping Zhuang, Run He, Kai Tong, Di Fang, Han Sun, Haoran Li, Tianyi Chen, Ziqian Zeng | 2024-05-26 | arXiv | https://github.com/ZHUANGHP/Analytic-federated-learning | https://doi.org/10.48550/arXiv.2405.16240 |
| 130 | Client2Vec: Improving Federated Learning by Distribution Shifts Aware Client Indexing | Yongxin Guo, Lin Wang, Xiaoying Tang, Tao Lin | 2024-05-26 | arXiv | https://github.com/LINs-lab/client2vec | https://doi.org/10.48550/arXiv.2405.16233 |
| 131 | FedSheafHN: Personalized Federated Learning on Graph-structured Data | Wenfei Liang, Yanan Zhao, Rui She, Yiming Li, Wee Peng Tay | 2024-05-26 | arXiv | https://github.com/CarrieWFF/ICML-2024-submission-recording/blob/main/Screenshot%20of%20FedSheafHN%20submission%20to%20ICML%202024.png | https://doi.org/10.48550/arXiv.2405.16056 |
| 132 | Vertical Federated Learning for Effectiveness, Security, Applicability: A Survey | Mang Ye, Wei Shen, Bo Du, Eduard Snezhko, Vassili Kovalev, Pong C. Yuen | 2024-05-26 | arXiv | https://github.com/shentt67/VFL_Survey | https://doi.org/10.48550/arXiv.2405.17495 |
| 133 | Massive Digital Over-the-Air Computation for Communication-Efficient Federated Edge Learning | Li Qiao, Zhen Gao, Mahdi Boloursaz Mashhadi, Deniz Gündüz | 2024-05-25 | IEEE Journal on Selected Areas in Communications | https://github.com/liqiao19/MD-AirComp | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10648926 |
| 134 | Thinking Forward: Memory-Efficient Federated Finetuning of Language Models | Kunjal Panchal, Nisarg Parikh, Sunav Choudhary, Lijun Zhang, Yuriy Brun, Hui Guan | 2024-05-25 | arXiv …, 2024 | https://github.com/Astuary/Spry | http://arxiv.org/abs/2405.15551v1 |
| 135 | Achieving Dimension-Free Communication in Federated Learning via Zeroth-Order Optimization | Zhe Li, Bicheng Ying, Zidong Liu, Chaosheng Dong, Haibo Yang | 2024-05-24 | arXiv | https://github.com/ZidongLiu/FedDisco | https://doi.org/10.48550/arXiv.2405.15861 |
| 136 | Federated Online Adaptation for Deep Stereo | Matteo Poggi, Fabio Tosi | 2024-05-23 | 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | https://fedstereo.github.io/ | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10658044 |
| 137 | EmInspector: Combating Backdoor Attacks in Federated Self-Supervised Learning Through Embedding Inspection | Yuwen Qian, Shuchi Wu, Kang Wei, Ming Ding, Di Xiao, Tao Xiang, Chuan Ma, Song Guo | 2024-05-21 | arXiv | https://github.com/ShuchiWu/EmInspector | https://doi.org/10.48550/arXiv.2405.13080 |
| 138 | Federated Learning for Time-Series Healthcare Sensing with Incomplete Modalities | Adiba Orzikulova, Jaehyun Kwak, Jaemin Shin, Sung-Ju Lee | 2024-05-20 | arXiv | https://github.com/AdibaOrz/FLISM | http://arxiv.org/abs/2405.11828v2 |
| 139 | A GAN-Based Data Poisoning Attack Against Federated Learning Systems and Its Countermeasure | Wei Sun, Bo Gao, Ke Xiong, Yuwei Wang | 2024-05-20 | arXiv | https://github.com/SSssWEIssSS/VagueGAN-Data-Poisoning-Attack-and-Its-Countermeasure | https://doi.org/10.48550/arXiv.2405.11440 |
| 140 | Feature-Based Federated Transfer Learning: Communication Efficiency, Robustness and Privacy | Feng Wang, Mustafa Cenk Gursoy, Senem Velipasalar | 2024-05-16 | IEEE Transactions on Machine Learning in Communications and Networking | https://github.com/wfwf10/Feature-based-Federated-Transfer-Learning | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10542971 |
| 141 | From Optimization to Generalization: Fair Federated Learning against Quality Shift via Inter-Client Sharpness Matching | Nannan Wu, Zhuo Kuang, Zengqiang Yan, Li Yu | 2024-04-27 | arXiv | https://github.com/wnn2000/FFL4MIA | https://doi.org/10.48550/arXiv.2404.17805 |
| 142 | Beyond Traditional Threats: A Persistent Backdoor Attack on Federated Learning | Tao Liu, Yuhang Zhang, Zhu Feng, Zhiqin Yang, Chen Xu, Dapeng Man, Wu Yang | 2024-04-26 | AAAI | https://github.com/PhD-TaoLiu/FCBA | https://doi.org/10.1609/aaai.v38i19.30131 |
| 143 | Decentralized Personalized Federated Learning based on a Conditional Sparse-to-Sparser Scheme | Qianyu Long, Qiyuan Wang, Christos Anagnostopoulos, Daning Bi | 2024-04-24 | arXiv | https://github.com/EricLoong/da-dpfl | https://doi.org/10.48550/arXiv.2404.15943 |
| 144 | On the Efficiency of Privacy Attacks in Federated Learning | Nawrin Tabassum, Ka-Ho Chow, Xuyu Wang, Wenbin Zhang, Yanzhao Wu | 2024-04-15 | 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) | https://github.com/mlsysx/EPAFL | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10677989 |
| 145 | Anti-Byzantine attacks enabled vehicle selection for asynchronous federated learning in vehicular edge computing | Cui Zhang, Xiao Xu, Qiong Wu, Pingyi Fan, Qiang Fan, Huiling Zhu, Jiangzhou Wang | 2024-04-12 | China Communications | https://github.com/giongwu86/By-AFLDDPG | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10670125 |
| 146 | FedSelect: Personalized Federated Learning with Customized Selection of Parameters for Fine-Tuning | Rishub Tamirisa, Chulin Xie, Wenxuan Bao, Andy Zhou, Ron Arel, Aviv Shamsian | 2024-04-03 | 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | https://github.com/lapisrocks/fedselect | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10658065 |
| 147 | A Practical Recipe for Federated Learning Under Statistical Heterogeneity Experimental Design | Mahdi Morafah, Weijia Wang, Bill Lin | 2024-04-01 | IEEE Transactions on Artificial Intelligence | https://github.com/MMorafah/FedZoo-Bench | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10189084 |
| 148 | No One Left Behind: Real-World Federated Class-Incremental Learning | Jiahua Dong, Yang Cong, Gan Sun, Yulun Zhang, Bernt Schiele, Dengxin Dai | 2024-04-01 | IEEE Transactions on Pattern Analysis and Machine Intelligence | https://github.com/JiahuaDong/LGA | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10323204 |
| 149 | Task-Agnostic Privacy-Preserving Representation Learning for Federated Learning Against Attribute Inference Attacks | Caridad Arroyo Arevalo, Sayedeh Leila Noorbakhsh, Yun Dong, Yuan Hong, Binghui Wang | 2024-03-25 | arXiv | https://github.com/TAPPFL | https://doi.org/10.48550/arXiv.2312.06989 |
| 150 | Resisting Backdoor Attacks in Federated Learning via Bidirectional Elections and Individual Perspective | Zhen Qin, Feiyi Chen, Chen Zhi, Xueqiang Yan, Shuiguang Deng | 2024-03-25 | arXiv | https://github.com/zhenqincn/Snowball | https://doi.org/10.48550/arXiv.2309.16456 |
| 151 | PPIDSG: A Privacy-Preserving Image Distribution Sharing Scheme with GAN in Federated Learning | Yuting Ma, Yuanzhi Yao, Xiaohua Xu | 2024-03-25 | arXiv | https://github.com/ytingma/PPIDSG | https://doi.org/10.48550/arXiv.2312.10380 |
| 152 | Federated Adaptive Prompt Tuning for Multi-Domain Collaborative Learning | Shangchao Su, Mingzhao Yang, Bin Li, Xiangyang Xue | 2024-03-25 | AAAI | https://github.com/leondada/FedAPT | https://doi.org/10.1609/aaai.v38i13.29434 |
| 153 | Federated Learning with Extremely Noisy Clients via Negative Distillation | Yang Lu, Lin Chen, Yonggang Zhang, Yiliang Zhang, Bo Han, Yiu-ming Cheung, Hanzi Wang | 2024-03-25 | arXiv | https://github.com/linChen99/FedNed | https://doi.org/10.48550/arXiv.2312.12703 |
| 154 | FedLPS: Heterogeneous Federated Learning for Multiple Tasks with Local Parameter Sharing | Yongzhe Jia, Xuyun Zhang, Amin Beheshti, Wanchun Dou | 2024-03-25 | AAAI | https://github.com/jyzgh/FedLPS | https://doi.org/10.1609/aaai.v38i11.29181 |
| 155 | FedTGP: Trainable Global Prototypes with Adaptive-Margin-Enhanced Contrastive Learning for Data and Model Heterogeneity in Federated Learning | Jianqing Zhang, Yang Liu, Yang Hua, Jian Cao | 2024-03-25 | AAAI | https://github.com/TsingZ0/FedTGP | https://doi.org/10.1609/aaai.v38i15.29617 |
| 156 | FedDiv: Collaborative Noise Filtering for Federated Learning with Noisy Labels | Jichang Li, Guanbin Li, Hui Cheng, Zicheng Liao, Yizhou Yu | 2024-03-25 | arXiv | https://github.com/lijichang/FLNL-FedDiv | https://doi.org/10.48550/arXiv.2312.12263 |
| 157 | Exploiting Label Skews in Federated Learning with Model Concatenation | Yiqun Diao, Qinbin Li, Bingsheng He | 2024-03-25 | arXiv | https://github.com/sjtudyq/FedConcat | https://doi.org/10.48550/arXiv.2312.06290 |
| 158 | Calibrated One Round Federated Learning with Bayesian Inference in the Predictive Space | Mohsin Hasan, Guojun Zhang, Kaiyang Guo, Xi Chen, Pascal Poupart | 2024-03-25 | arXiv | https://github.com/hasanmohsin/betaPredBayesFL | https://doi.org/10.48550/arXiv.2312.09817 |
| 159 | An Upload-Efficient Scheme for Transferring Knowledge From a Server-Side Pre-trained Generator to Clients in Heterogeneous Federated Learning | Jianqing Zhang, Yang Liu, Yang Hua, Jian Cao | 2024-03-23 | 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | https://github.com/TsingZ0/FedKTL | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10658581 |
| 160 | Efficiently Assemble Normalization Layers and Regularization for Federated Domain Generalization | Khiem Le, Long Ho, Cuong Do, Danh Le-Phuoc, Kok-Seng Wong | 2024-03-22 | 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | https://github.com/lhkhiem28/gPerXAN | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10658093 |
| 161 | Text-Enhanced Data-Free Approach for Federated Class-Incremental Learning | Minh-Tuan Tran, Trung Le, Xuan-May Thi Le, Mehrtash Harandi, Dinh Phung | 2024-03-21 | 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | https://github.com/tmtuan1307/lander | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10656385 |
| 162 | Fed3DGS: Scalable 3D Gaussian Splatting with Federated Learning | Teppei Suzuki | 2024-03-18 | arXiv | https://github.com/DensoITLab/Fed3DGS | https://doi.org/10.48550/arXiv.2403.11460 |
| 163 | FedFMS: Exploring Federated Foundation Models for Medical Image Segmentation | Yuxi Liu, Guibo Luo, Yuesheng Zhu | 2024-03-08 | arXiv | https://github.com/LIU-YUXI/FedFMS | http://arxiv.org/abs/2403.05408v1 |
| 164 | FLGuard: Byzantine-Robust Federated Learning via Ensemble of Contrastive Models | Younghan Lee, Yungi Cho, Woorim Han, Ho Bae, Yunheung Paek | 2024-03-05 | ESORICS | https://github.com/201younghanlee/FLGuard | https://doi.org/10.1007/978-3-031-51482-1_4 |
| 165 | Towards Optimal Customized Architecture for Heterogeneous Federated Learning with Contrastive Cloud-Edge Model Decoupling | Xingyan Chen, Tian Du, Mu Wang, Tiancheng Gu, Yu Zhao, Gang Kou, Changqiao Xu, Dapeng Oliver Wu | 2024-03-04 | arXiv | https://github.com/elegy112138/FedCMD | https://doi.org/10.48550/arXiv.2403.02360 |
| 166 | EcoFed: Efficient Communication for DNN Partitioning-Based Federated Learning | Di Wu, Rehmat Ullah, Philip Rodgers, Peter Kilpatrick, Ivor T. A. Spence, Blesson Varghese | 2024-03-01 | IEEE Transactions on Parallel and Distributed Systems | https://github.com/blessonvar/EcoFed | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10380682 |
| 167 | Rethinking Data Heterogeneity in Federated Learning: Introducing a New Notion and Standard Benchmarks | Mahdi Morafah, Saeed Vahidian, Chen Chen, Mubarak Shah, Bill Lin | 2024-03-01 | IEEE Transactions on Artificial Intelligence | https://github.com/MMorafah/FL-SC-NIID | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10174745 |
| 168 | Memory-based optimization methods for model-agnostic meta-learning and personalized federated learning | Bokun Wang, Zhuoning Yuan, Yiming Ying, Tianbao Yang | 2024-03 | The Journal of Machine Learning Research (JMLR), Volume 24, Issue 1 | https://github.com/bokun-wang/moml | https://dl.acm.org/doi/10.5555/3648699.3648844 |
| 169 | Uncertainty-Based Extensible Codebook for Discrete Federated Learning in Heterogeneous Data Silos | Tianyi Zhang, Yu Cao, Dianbo Liu | 2024-02-29 | arXiv | https://github.com/destiny301/uefl | https://doi.org/10.48550/arXiv.2402.18888 |
| 170 | CoDream: Exchanging dreams instead of models for federated aggregation with heterogeneous models | Abhishek Singh, Gauri Gupta, Ritvik Kapila, Yichuan Shi, Alex Dang, Sheshank Shankar, Mohammed Ehab, Ramesh Raskar | 2024-02-25 | arXiv | https://mitmedialab.github.io/codream.github.io/ | http://arxiv.org/abs/2402.15968v2 |
| 171 | Fedkit: Enabling Cross-Platform Federated Learning for Android and iOS | Sichang He, Beilong Tang, Boyan Zhang, Jiaoqi Shao, Xiaomin Ouyang, Daniel Nata Nugraha, Bing Luo | 2024-02-16 | IEEE INFOCOM 2024 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) | https://github.com/FedCampus/FedKit | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10620662 |
| 172 | Evaluating Membership Inference Attacks and Defenses in Federated Learning | Gongxi Zhu, Donghao Li, Hanlin Gu, Yuxing Han, Yuan Yao, Lixin Fan, Qiang Yang | 2024-02-09 | arXiv | https://github.com/Liar-Mask/FedMIA | https://doi.org/10.48550/arXiv.2402.06289 |
| 173 | FedBoosting: Federated learning with gradient protected boosting for text recognition | Hanchi Ren, Jingjing Deng, Xianghua Xie, Xiaoke Ma, Yichuan Wang | 2024-02-07 | Neurocomputing | https://github.com/Rand2AI/FedBoosting | https://doi.org/10.1016/j.neucom.2023.127126 |
| 174 | Federated Learning with New Knowledge: Fundamentals, Advances, and Futures | Lixu Wang, Yang Zhao, Jiahua Dong, Ating Yin, Qinbin Li, Xiao Wang, Dusit Niyato, Qi Zhu | 2024-02-03 | arXiv | https://github.com/conditionWang/FLNK | https://doi.org/10.48550/arXiv.2402.02268 |
| 175 | FedSarah: A Novel Low-Latency Federated Learning Algorithm for Consumer-Centric Personalized Recommendation Systems | Zhiguo Qu, Jian Ding, Rutvij H. Jhaveri, Youcef Djenouri, Xin Ning, Prayag Tiwari | 2024-02-01 | IEEE Transactions on Consumer Electronics | https://github.com/DashingJ-82/FedSarah | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10354460 |
| 176 | Federated Semi-Supervised Medical Image Segmentation via Prototype-Based Pseudo-Labeling and Contrastive Learning | Huisi Wu, Baiming Zhang, Cheng Chen, Jing Qin | 2024-02-01 | IEEE Transactions on Medical Imaging | https://github.com/zhangbaiming/FedSemiSeg | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10250843 |
| 177 | Generalizable Heterogeneous Federated Cross-Correlation and Instance Similarity Learning | Wenke Huang, Mang Ye, Zekun Shi, Bo Du | 2024-02-01 | IEEE Transactions on Pattern Analysis and Machine Intelligence | https://github.com/WenkeHuang/FCCL | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10295990 |
| 178 | Secure Federated Learning With Fully Homomorphic Encryption for IoT Communications | Neveen Mohammad Hijazi, Moayad Aloqaily, Mohsen Guizani, Bassem Ouni, Fakhri Karray | 2024-02-01 | IEEE Internet of Things Journal | https://github.com/Artifitialleap-MBZUAI/Secure-Federated-Learning-with-Fully-Homomorphic-Encryption-for-IoT-Communications | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10208145 |
| 179 | FedCore: Straggler-Free Federated Learning with Distributed Coresets | Hongpeng Guo, Haotian Gu, Xiaoyang Wang, Bo Chen, Eun Kyung Lee, Tamar Eilam, Deming Chen, Klara Nahrstedt | 2024-01-31 | ICC 2024 - IEEE International Conference on Communications | https://github.com/hongpeng-guo/PedCore | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10622224 |
| 180 | Spectral Co-Distillation for Personalized Federated Learning | Zihan Chen, Howard H. Yang, Tony Q. S. Quek, Kai Fong Ernest Chong | 2024-01-29 | NeurIPS | https://github.com/jimmyc96/spectral-dis-FL | http://papers.nips.cc/paper_files/paper/2023/hash/1b86cf4b15cd83b6520d851eb7298228-Abstract-Conference.html |
| 181 | FedRSU: Federated Learning for Scene Flow Estimation on Roadside Units | Shaoheng Fang, Rui Ye, Wenhao Wang, Zuhong Liu, Yuxiao Wang, Yafei Wang, Siheng Chen, Yanfeng Wang | 2024-01-23 | IEEE Transactions on Intelligent Transportation Systems | https://github.com/wwh0411/FedRSU | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10648899 |
| 182 | Privacy-Preserving Individual-Level COVID-19 Infection Prediction via Federated Graph Learning | Wenjie Fu, Huandong Wang, Chen Gao, Guanghua Liu, Yong Li, Tao Jiang | 2024-01-22 | ACM Transactions on Information Systems (TOIS), Volume 42, Issue 3 | https://github.com/wjfu99/FL-epidemic | https://dl.acm.org/doi/10.1145/3633202 |
| 183 | Cooperative Edge Caching Based on Elastic Federated and Multi-Agent Deep Reinforcement Learning in Next-Generation Networks | Qiong Wu, Wenhua Wang, Pingyi Fan, Qiang Fan, Huiling Zhu, Khaled B. Letaief | 2024-01-18 | IEEE Transactions on Network and Service Management | https://github.com/qiongwu86/Edge-Caching-Based-on-Multi-Agent-Deep-Reinforcement-Learning-and-Federated-Learning | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10536013 |
| 184 | FedLoGe: Joint Local and Generic Federated Learning under Long-tailed Data | Zikai Xiao, Zihan Chen, Liyinglan Liu, Yang Feng, Jian Wu, Wanlu Liu, Joey Tianyi Zhou, Howard Hao Yang, Zuozhu Liu | 2024-01-17 | arXiv | https://github.com/ZackZikaiXiao/FedLoGe | https://doi.org/10.48550/arXiv.2401.08977 |
| 185 | Relaxed Contrastive Learning for Federated Learning | Seonguk Seo, Jinkyu Kim, Geeho Kim, Bohyung Han | 2024-01-10 | 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | https://github.com/skynbe/FedRCL: | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10658073 |
| 186 | Improving Transferability of Network Intrusion Detection in a Federated Learning Setup | Shreya Ghosh, Abu Shafin Mohammad Mahdee Jameel, Aly El Gamal | 2024-01-07 | 2024 IEEE International Conference on Machine Learning for Communication and Networking (ICMLCN) | https://github.com/ghosh64/transferability | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10624761 |
| 187 | Mitigation of Gradient Inversion Attacks in Federated Learning with Private Adaptive Optimization | Cody Lewis, Vijay Varadharajan, Nasimul Noman, Udaya Kiran Tupakula, Nan Li | 2024-01-01 | 2024 IEEE 44th International Conference on Distributed Computing Systems (ICDCS) | https://github.com/codymlewis/SecOpt | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10631001 |
| 188 | FedLSF: Federated Local Graph Learning via Specformers | Ram Samarth BB, Annappa B, Sachin D. N | 2024-01-01 | 2024 20th International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT) | https://github.com/achiverram28/FedLSF-DCOSS | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10621457 |
| 189 | FedPKR: Federated Learning With Non-IID Data Via Periodic Knowledge Review in Edge Computing | J. Wang, R. Wang, G. Xu, D. He, X. Pei, F. Zhang, J. Gan | 2024-01-01 | IEEE Transactions on Sustainable Computing | https://github.com/jbwangnb/FedPKR | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10461059 |
| 190 | FedRC: Tackling Diverse Distribution Shifts Challenge in Federated Learning by Robust Clustering | Yongxin Guo, Xiaoying Tang, Tao Lin | 2024-01-01 | ICML | https://github.com/LINs-lab/FedRC | https://openreview.net/forum?id=kc4dZYJlJG |
| 191 | Federated Learning for Vehicle Trajectory Prediction: Methodology and Benchmark Study | Hongye Wang, Ruonan Li, Zenglin Xu, JinLong Li, Irwin King, Jie Liu | 2024-01-01 | 2024 International Joint Conference on Neural Networks (IJCNN) | https://github.com/FedVTP/FedVTP | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10650788 |
| 192 | Federated Learning via Consensus Mechanism on Heterogeneous Data: A New Perspective on Convergence | Shu Zheng, Tiandi Ye, Xiang Li, Ming Gao | 2024-01-01 | ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) | https://github.com/fedcome/fedcome | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10446892 |
| 193 | Federated Multimodal and Multiresolution Graph Integration for Connectional Brain Template Learning | Jia Ji, Islem Rekik | 2024-01-01 | DGM4MICCAI | https://github.com/basiralab/Fed2M | https://doi.org/10.1007/978-3-031-53767-7_2 |
| 194 | GFS: Gradient-Based Fairness-Aware Client Selection for Federated Learning | Z. Wang, D. Xiao, D. Yang, W. Wu | 2024-01-01 | 2024 9th International Conference on Cloud Computing and Big Data Analytics (ICCCBDA) | https://github.com/SelectionStrategy/GFS_Strategy | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10569535 |
| 195 | Guard-FL: An UMAP-Assisted Robust Aggregation for Federated Learning | Anxiao Song, Haoshuo Li, Ke Cheng, Tao Zhang, Aijing Sun, Yulong Shen | 2024-01-01 | IEEE Internet of Things Journal | https://github.com/XidianNSS/Guard-FL | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10529118 |
| 196 | Internal Cross-layer Gradients for Extending Homogeneity to Heterogeneity in Federated Learning | Yun-Hin Chan, Rui Zhou, Running Zhao, Zhihan Jiang, Edith C. -H. Ngai | 2024-01-01 | arXiv | https://github.com/ChanYunHin/InCo-Aggregation | https://doi.org/10.48550/arXiv.2308.11464 |
| 197 | Maximum Knowledge Orthogonality Reconstruction with Gradients in Federated Learning | Feng Wang, Senem Velipasalar, Mustafa Cenk Gursoy | 2024-01-01 | 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) | https://github.com/wfwf10/MKOR | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10484110 |
| 198 | MetaVers: Meta-Learned Versatile Representations for Personalized Federated Learning | Jin Hyuk Lim, SeungBum Ha, Sung Whan Yoon | 2024-01-01 | 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) | https://github.com/eepLearning/MetaVers | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10484206 |
| 199 | Personalized Privacy-Preserving Framework for Cross-Silo Federated Learning | Van Tuan Tran, Huy Hieu Pham, Kok-Seng Wong | 2024-01-01 | IEEE Transactions on Emerging Topics in Computing | http://github.com/github.com/vinuni-vishc/PPPF-Cross-Silo-FL | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10418075 |
| 200 | Physics-Driven Spectrum-Consistent Federated Learning for Palmprint Verification | Ziyuan Yang, Andrew Beng Jin Teoh, Bob Zhang, Lu Leng, Yi Zhang | 2024-01-01 | arXiv | https://github.com/Zi-YuanYang/PSFed-Palm | https://doi.org/10.48550/arXiv.2308.00451 |
| 201 | Post-Deployment Adaptation with Access to Source Data via Federated Learning and Source-Target Remote Gradient Alignment | Felix Wagner, Zeju Li, Pramit Saha, Konstantinos Kamnitsas | 2024-01-01 | MLMI@MICCAI | https://github.com/FelixWag/StarAlign | https://doi.org/10.1007/978-3-031-45676-3_26 |
| 202 | FedFusion: Manifold-Driven Federated Learning for Multi-Satellite and Multi-Modality Fusion | Daixun Li, Weiying Xie, Yunsong Li, Leyuan Fang | 2024-01-01 | IEEE Transactions on Geoscience and Remote Sensing | https://github.com/LDXDU/FedFusion | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10342879 |
| 203 | RoseAgg: Robust Defense Against Targeted Collusion Attacks in Federated Learning | He Yang, Wei Xi, Yuhao Shen, Canhui Wu, Jizhong Zhao | 2024-01-01 | IEEE Transactions on Information Forensics and Security | https://github.com/SleepedCat/RoseAgg | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10387506 |
| 204 | Semi-Asynchronous Federated Learning with Trajectory Prediction for Vehicular Edge Computing | Yuxuan Deng, Xiuhua Li, Chuan Sun, Qilin Fan, Xiaofei Wang, Victor C. M. Leung | 2024-01-01 | 2024 IEEE/ACM 32nd International Symposium on Quality of Service (IWQoS) | https://github.com/dyxcode/Semi-Asynchronous-Federated-Learning | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10682953 |
| 205 | Subgraph Federated Learning with Global Graph Reconstruction | Zhi Liu, Hanlin Zhou, Feng Xia, Guojiang Shen, Vidya Saikrishna, Xiaohua He, Jiaxin Du, Xiangjie Kong | 2024-01-01 | Web and Big Data | https://github.com/poipoipoi233/FedGGR | http://dx.doi.org/10.1007/978-981-97-2303-4_11 |
| 206 | UPFL: Unsupervised Personalized Federated Learning towards New Clients | Tiandi Ye, Cen Chen, Yinggui Wang, Xiang Li, Ming Gao | 2024-01-01 | arXiv | https://github.com/anonymous-federated-learning/code | https://doi.org/10.48550/arXiv.2307.15994 |
| 207 | Unveiling Backdoor Risks Brought by Foundation Models in Heterogeneous Federated Learning | Xi Li, Chen Wu, Jiaqi Wang | 2024-01-01 | arXiv | https://github.com/lixi1994/backdoor_FM_hete_FL | https://doi.org/10.48550/arXiv.2311.18350 |
| 208 | Use of Federated Learning for Personal Smart Media Cloud Solutions | B. Kumarage, H. Harankahadeniya, A. Induranga, I. Perera, K. Gunasekera | 2024-01-01 | 2024 Moratuwa Engineering Research Conference (MERCon) | https://github.com/PicsSmart | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10688883 |
| 209 | VFLAIR: A Research Library and Benchmark for Vertical Federated Learning | Tianyuan Zou, Zixuan Gu, Yu He, Hideaki Takahashi, Yang Liu, Guangnan Ye, Ya-Qin Zhang | 2024-01-01 | arXiv | https://github.com/FLAIR-THU/VFLAIR | https://doi.org/10.48550/arXiv.2310.09827 |
| 210 | WeightRelay: Efficient Heterogeneous Federated Learning on Time Series | Wensi Tang, Guodong Long | 2024-01-01 | AI | https://github.com/Wensi-Tang/DPSN/blob/master/AJCAI23_wensi_fedTSC.pdf | https://doi.org/10.1007/978-981-99-8388-9_11 |
| 211 | FedGR: Genetic Algorithm and Relay Strategy Based Federated Learning | Yifei Zeng, Kai Zhao, Fangchao Yu, Bo Zeng, Zhi Pang, Lina Wang | 2024-01-01 | 2024 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD) | https://github.com/zyfhylyh/FedGR | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10580045 |
| 212 | Replica-Based Federated Learning with Heterogeneous Architectures for Graph Super-Resolution | Ramona Ghilea, Islem Rekik | 2024-01-01 | MLMI@MICCAI | https://github.com/basiralab/RepFL | https://doi.org/10.1007/978-3-031-45676-3_28 |
| 213 | FedER: Federated Learning through Experience Replay and privacy-preserving data synthesis | Matteo Pennisi, Federica Proietto Salanitri, Giovanni Bellitto, Bruno Casella, Marco Aldinucci, Simone Palazzo, Concetto Spampinato | 2024-01-01 | Comput. Vis. Image Underst. | https://github.com/perceivelab/FedER | https://doi.org/10.1016/j.cviu.2023.103882 |
| 214 | BOBA: Byzantine-Robust Federated Learning with Label Skewness | Wenxuan Bao, Jun Wu, Jingrui He | 2024-01-01 | arXiv | https://github.com/baowenxuan/BOBA | https://doi.org/10.48550/arXiv.2208.12932 |
| 215 | FedDBL: Communication and Data Efficient Federated Deep-Broad Learning for Histopathological Tissue Classification | Tianpeng Deng, Yanqi Huang, Zhenwei Shi, Jiatai Lin, Qi Dou, Ke Zhao, Fang-Fang Liu, Yu-Mian Jia, Jin Wang, Bingchao Zhao, Changhong Liang, Zaiyi Liu, Xiao-jing Guo, Guoqiang Han, Xin Chen, Chu Han | 2024-01-01 | IEEE Transactions on Cybernetics | https://github.com/tianpeng-deng/FedDBL | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10572001 |
| 216 | Understanding and Improving Model Averaging in Federated Learning on Heterogeneous Data | Tailin Zhou, Zehong Lin, Jun Zhang, Danny H. K. Tsang | 2024-01-01 | IEEE Transactions on Mobile Computing | https://github.com/TailinZhou/FedIMA | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10540229 |
| 217 | Cross-Modal Vertical Federated Learning for MRI Reconstruction | Yunlu Yan, Hong Wang, Yawen Huang, Nanjun He, Lei Zhu, Yong Xu, Yuexiang Li, Yefeng Zheng | 2024-01-01 | IEEE Journal of Biomedical and Health Informatics | https://github.com/IAMJackYan/FedCRFD | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10417111 |
| 218 | A Hybrid Self-Supervised Learning Framework for Vertical Federated Learning | Yuanqin He, Yan Kang, Xinyuan Zhao, Jiahuan Luo, Lixin Fan, Yuxing Han, Qiang Yang | 2024-01-01 | IEEE Transactions on Big Data | https://github.com/jorghyq2016/FedHSSL | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10535420 |
| 219 | A Robust Detection and Correction Framework for GNN-Based Vertical Federated Learning | Zhicheng Yang, Xiaoliang Fan, Zheng Wang, Zihui Wang, Cheng Wang | 2024-01-01 | PRCV | https://github.com/zcyang-cs/RDC-GVFL | https://doi.org/10.1007/978-981-99-8435-0_8 |
| 220 | ALI-DPFL: Differentially Private Federated Learning with Adaptive Local Iterations | Xinpeng Ling, Jie Fu, Kuncan Wang, Haitao Liu, Zhili Chen | 2024-01-01 | 2024 IEEE 25th International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM) | https://github.com/KnightWan/ALI-DPFL | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10579181 |
| 221 | Agglomerative Federated Learning: Empowering Larger Model Training via End-Edge-Cloud Collaboration | Zhiyuan Wu, Sheng Sun, Yuwei Wang, Min Liu, Bo Gao, Quyang Pan, Tianliu He, Xuefeng Jiang | 2024-01-01 | IEEE INFOCOM 2024 - IEEE Conference on Computer Communications | https://github.com/wuzhiyuan2000/FedAgg | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10621254 |
| 222 | Aggregation-Assisted Proxyless Distillation: A Novel Approach for Handling System Heterogeneity in Federated Learning | Nirbhay Sharma, Mayank Raj, Deepak Mishra | 2024-01-01 | 2024 International Joint Conference on Neural Networks (IJCNN) | https://github.com/nirbhay-design/FedAgPD | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10650564 |
| 223 | ArtFL: Exploiting Data Resolution in Federated Learning for Dynamic Runtime Inference via Multi-Scale Training | Siyang Jiang, Xian Shuai, Guoliang Xing | 2024-01-01 | 2024 23rd ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN) | https://github.com/siyang-jiang/ArtFL.git.CCS | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10577356 |
| 224 | Attentive Modeling and Distillation for Out-of-Distribution Generalization of Federated Learning | Zhuang Qi, Weihao He, Xiangxu Meng, Lei Meng | 2024-01-01 | 2024 IEEE International Conference on Multimedia and Expo (ICME) | https://github.com/qizhuang-qz/FedAKD | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10687423 |
| 225 | BM-FL: A Balanced Weight Strategy for Multi-stage Federated Learning Against Multi-client Data Skewing | Lixiang Yuan, Mingxing Duan, Guoqing Xiao, Zhuo Tang, Kenli Li | 2024-01-01 | IEEE Transactions on Knowledge and Data Engineering | https://github.com/ylxzjy/BMFL | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10458321 |
| 226 | Federated Learning for Generalization, Robustness, Fairness: A Survey and Benchmark | Wenke Huang, Mang Ye, Zekun Shi, Guancheng Wan, He Li, Bo Du, Qiang Yang | 2024-01-01 | IEEE Transactions on Pattern Analysis and Machine Intelligence | https://github.com/WenkeHuang/MarsFL | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10571602 |
| 227 | Blades: A Unified Benchmark Suite for Byzantine Attacks and Defenses in Federated Learning | Shenghui Li, Edith C. H. Ngai, Fanghua Ye, Li Ju, Tianru Zhang, Thiemo Voigt | 2024-01-01 | 2024 IEEE/ACM Ninth International Conference on Internet-of-Things Design and Implementation (IoTDI) | https://github.com/lishenghui/blades | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10562176 |
| 228 | FLTracer: Accurate Poisoning Attack Provenance in Federated Learning | Xinyu Zhang, Qingyu Liu, Zhongjie Ba, Yuan Hong, Tianhang Zheng, Feng Lin, Li Lu, Kui Ren | 2024-01-01 | IEEE Transactions on Information Forensics and Security | https://github.com/Eyr3/FLTracer | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10549523 |
| 229 | Defending Against Data and Model Backdoor Attacks in Federated Learning | H. Wang, X. Mu, D. Wang, Q. Xu, K. Li | 2024-01-01 | IEEE Internet of Things Journal | https://github.com/whwh456/TSF | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10559965 |
| 230 | FedCompass: Efficient Cross-Silo Federated Learning on Heterogeneous Client Devices using a Computing Power Aware Scheduler | Zilinghan Li, Pranshu Chaturvedi, Shilan He, Han Chen, Gagandeep Singh, Volodymyr V. Kindratenko, Eliu A. Huerta, Kibaek Kim, Ravi K. Madduri | 2024-01-01 | arXiv | https://github.com/APPFL/FedCompass | https://doi.org/10.48550/arXiv.2309.14675 |
| 231 | FedBEVT: Federated Learning Bird's Eye View Perception Transformer in Road Traffic Systems | Rui Song, Runsheng Xu, Andreas Festag, Jiaqi Ma, Alois C. Knoll | 2024-01-01 | IEEE Transactions on Intelligent Vehicles | https://github.com/rruisong/FedBEVT | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10236488 |
| 232 | Fed-MS: Fault Tolerant Federated Edge Learning with Multiple Byzantine Servers | Senmao Qi, Hao Ma, Yifei Zou, Yuan Yuan, Peng Li, Dongxiao Yu | 2024-01-01 | 2024 IEEE 44th International Conference on Distributed Computing Systems (ICDCS) | https://github.com/haoma2772/Fed-MS | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10631004 |
| 233 | FedCache: A Knowledge Cache-Driven Federated Learning Architecture for Personalized Edge Intelligence | Zhiyuan Wu, Sheng Sun, Yuwei Wang, Min Liu, Ke Xu, Wen Wang, Xuefeng Jiang, Bo Gao, Jinda Lu | 2024-01-01 | IEEE Transactions on Mobile Computing | https://github.com/wuzhiyuan2000/FedCache | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10420495 |
| 234 | FKD-Med: Privacy-Aware, Communication-Optimized Medical Image Segmentation via Federated Learning and Model Lightweighting Through Knowledge Distillation | Guanqun Sun, Han Shu, Feihe Shao, Teeradaj Racharak, Weikun Kong, Yizhi Pan, Jingjing Dong, Shuang Wang, Le-Minh Nguyen, Junyi Xin | 2024-01-01 | IEEE Access | https://github.com/SUN-1024/FKD-Med | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10456909 |
| 235 | FADngs: Federated Learning for Anomaly Detection | B. Dong, D. Chen, Y. Wu, S. Tang, Y. Zhuang | 2024-01-01 | IEEE Transactions on Neural Networks and Learning Systems | https://github.com/kanade00/Federated_Anomaly_detection | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10409269 |
| 236 | Distributed Collapsed Gibbs Sampler for Dirichlet Process Mixture Models in Federated Learning | Reda Khoufache, Mustapha Lebbah, Hanene Azzag, Étienne Goffinet, Djamel Bouchaffra | 2024-01-01 | arXiv | https://github.com/redakhoufache/DisCGS | https://doi.org/10.48550/arXiv.2312.11169 |
| 237 | Demo: Visualizing the Shadows: Unveiling Data Poisoning Behaviors in Federated Learning | Xueqing Zhang, Junkai Zhang, Ka-Ho Chow, Juntao Chen, Ying Mao, Mohamed Rahouti, Xiang Li, Yuchen Liu, Wenqi Wei | 2024-01-01 | 2024 IEEE 44th International Conference on Distributed Computing Systems (ICDCS) | https://github.com/CathyXueqingZhang/DataPoisoningVis | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10631025 |
| 238 | Recommendation of Electronic Mobile Gadgets Using Infused Decision Score With Mobile Radiation and Federated Sentiment Score | A. Kanapala, S. Dara, J. Sreedhar, A. Vidyarthi, D. Gupta, P. Gupta | 2024 | IEEE Transactions on Consumer Electronics | https://github.com/AnkitVidyarthi/Recommendation | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10382180 |
| 239 | GI-PIP: Do We Require Impractical Auxiliary Dataset for Gradient Inversion Attacks? | Y. Sun, G. Xiong, X. Yao, K. Ma, J. Cui | 2024 | ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) | https://github.com/D1aoBoomm/GI-PIP | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10445924 |
| 240 | HGTA: News Recommendation Based on Hierarchical Granular Semantic Embeddings and Threshold Attention | Y. Li, Z. Yang, Z. Li, X. Li | 2024 | 2024 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD) | https://github.com/liyiweneven/HGTA | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10580511 |
| 241 | Heterogeneous Federated Learning: State-of-the-art and Research Challenges | Mang Ye, Xiuwen Fang, Bo Du, Pong C. Yuen, Dacheng Tao | 2024 | ACM Computing Surveys (CSUR), Volume 56, Issue 3 | https://github.com/marswhu/HFL_Survey | https://dl.acm.org/doi/10.1145/3625558 |
| 242 | Hide Your Model: A Parameter Transmission-free Federated Recommender System | Wei Yuan, Chaoqun Yang, Liang Qu, Quoc Viet Hung Nguyen, Jianxin Li, Hongzhi Yin | 2024 | 2024 IEEE 40th International Conference on Data Engineering (ICDE) | https://github.com/hi-weiyuan/PTF-FedRec | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10597708 |
| 243 | Improving Plasticity in Online Continual Learning via Collaborative Learning | M. Wang, N. Michel, L. Xiao, T. Yamasaki | 2024 | 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | https://github.com/maorong-wang/CCL-DC | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10656781 |
| 244 | Labels Are Culprits: Defending Gradient Attack on Privacy | Z. Li, L. Wang, Z. Gu, Y. Lv, Z. Tian | 2024 | IEEE Internet of Things Journal | https://github.com/zhaohuali/Label-based-Defense | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10252047 |
| 245 | Meta-Knowledge Enhanced Data Augmentation for Federated Person Re-Identification | C. Song, X. Chen, W. Zhu, Y. Zhou, X. Gu, B. Li | 2024 | ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) | https://github.com/songchunli1999/MEDA | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10447543 |
| 246 | Perada: Parameter-Efficient Federated Learning Personalization with Generalization Guarantees | Chulin Xie, De-An Huang, Wenda Chu, Daguang Xu, Chaowei Xiao, Bo Li, Anima Anandkumar | 2024 | 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | https://github.com/NVlabsIPerAda | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10656007 |
| 247 | Privacy-Preserving Continual Federated Clustering via Adaptive Resonance Theory | Naoki Masuyama, Yusuke Nojima, Yuichiro Toda, Chu Kiong Loo, Hisao Ishibuchi, Naoyuki Kubota | 2024 | IEEE Access | https://github.com/Masuyama-lab/FCAC | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10689590 |
| 248 | Towards Building The Federatedgpt: Federated Instruction Tuning | Jianyi Zhang, Saeed Vahidian, Martin Kuo, Chunyuan Li, Ruiyi Zhang, Tong Yu, Yufan Zhou, Guoyin Wang, Yiran Chen | 2024 | ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) | https://github.com/JayZhang42/FederatedGPT-Shepherd | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10447454 |
| 249 | Reducing Non-IID Effects in Federated Autonomous Driving with Contrastive Divergence Loss | Tuong Do, Binh X. Nguyen, Hien Nguyen, Erman Tjiputra, Quang D. Tran, Te-Chuan Chiu, Anh Nguyen | 2024 | 2024 IEEE International Conference on Robotics and Automation (ICRA) | https://github.com/aioz-ai/CDL | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10611202 |
| 250 | Reliable Federated Disentangling Network for Non-IID Domain Feature | Meng Wang, Kai Yu, Chun-Mei Feng, Yiming Qian, Ke Zou, Lianyu Wang, Rick Siow Mong Goh, Yong Liu, Huazhu Fu | 2024 | IEEE Transactions on Big Data | https://github.com/LooKing9218/RFedDis | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10587114 |
| 251 | SHELOB-FFL: addressing Systems HEterogeneity with LOcally Backpropagated Forward-Forward Learning | S. Izzo, F. Giampaolo, D. Chiaro, F. Piccialli | 2024 | 2024 IEEE 44th International Conference on Distributed Computing Systems Workshops (ICDCSW) | https://github.com/MODALUNINA/SHELOB_FFL | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10661016 |
| 252 | Think Twice Before Selection: Federated Evidential Active Learning for Medical Image Analysis with Domain Shifts | Jiayi Chen, Benteng Ma, Hengfei Cui, Yong Xia, Kwang-Ting Cheng | 2024 | 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | https://github.com/JiayiChen815/FEAL | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10656006 |
| 253 | Towards More Effective and Transferable Poisoning Attacks against Link Prediction on Graphs | B. Tian, L. Zang, H. Fu, J. Han, S. Hu | 2024 | 2024 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD) | https://github.com/anonymousaccept/STAA | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10580418 |
| 254 | Traceable Federated Continual Learning | Qiang Wang, Bingyan Liu, Yawen Li | 2024 | 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | https://github.com/POwerWeirdo/TagFCL | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10658168 |
| 255 | Triple GNNs: Introducing Syntactic and Semantic Information for Conversational Aspect-Based Quadruple Sentiment Analysis | B. Li, Y. Li, S. Jia, B. Ma, Y. Ding, Z. Qi, X. Tan, M. Guo, S. Liu | 2024 | 2024 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD) | https://github.com/ | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10580730 |
| 256 | Understanding the Role of Layer Normalization in Label-Skewed Federated Learning | Guojun Zhang, Mahdi Beitollahi, Alex Bie, Xi Chen | 2024 | Trans. Mach. Learn. Res. | https://github.com/huawei-noah/Federated-Learning/tree/main/Layer_Normalization | https://openreview.net/forum?id=6BDHUkSPna |
| 257 | Unlocking the Potential of Federated Learning: The Symphony of Dataset Distillation via Deep Generative Latents | Yuqi Jia, Saeed Vahidian, Jingwei Sun, Jianyi Zhang, Vyacheslav Kungurtsev, Neil Zhenqiang Gong, Yiran Chen | 2024 | arXiv | https://github.com/FedDG23/FedDG-main | https://doi.org/10.48550/arXiv.2312.01537 |
| 258 | Fedsoda: Federated Cross-Assessment and Dynamic Aggregation for Histopathology Segmentation | Yuan Zhang, Yaolei Qi, Xiaoming Qi, Lotfi Senhadji, Yongyue Wei, Feng Chen, Guanyu Yang | 2024 | ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) | https://github.com/yuanzhang7/FedSODA | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10447912 |
| 259 | Fine-grained classification for aero-engine borescope images based on the fusion of local and global features | R. Huang, J. Zeng, X. Cheng, J. Wei | 2024 | 2024 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD) | https://github.com/LonelyProceduralApe/LG_fusion | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10580812 |
| 260 | Federated Generalized Category Discovery | N. Pu, W. Li, X. Ji, Y. Qin, N. Sebe, Z. Zhong | 2024 | 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | https://github.com/TPCD/FedGCD | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10655031 |
| 261 | Federated Learning with Convex Global and Local Constraints | Chuan He, Le Peng, Ju Sun | 2024 | Trans. Mach. Learn. Res. | https://github.com/PL97/Constr_FL | https://openreview.net/forum?id=qItxVbWyfe |
| 262 | Communication-Efficient Federated Learning with Accelerated Client Gradient | Geeho Kim, Jinkyu Kim, Bohyung Han | 2024 | 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | https://github.com/geehokim/FedACG: | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10656666 |
| 263 | MetaFed: Federated Learning Among Federations With Cyclic Knowledge Distillation for Personalized Healthcare | Yiqiang Chen, Wang Lu, Xin Qin, Jindong Wang, Xing Xie | 2024 | IEEE Transactions on Neural Networks and Learning Systems | https://github.com/microsoft/PersonalizedFL | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10197230 |
| 264 | A Federated Graph to Embedding Approach for Knowledge Graph Completion | H. Sun, X. Bi, D. Sui, Z. Tu | 2024 | ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) | https://github.com/s460305450/FedGE | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10446731 |
| 265 | A Riemannian Augmented Lagrangian Method for Structured Sparse PCA | C. Huang, P. Shang, X. Xiu | 2024 | 2024 43rd Chinese Control Conference (CCC) | https://github.com/ChenyiHuang23 | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10661785 |
| 266 | AEDD:Anomaly Edge Detection Defense for Visual Recognition in Autonomous Vehicle Systems | L. Wang, J. Zhou, D. Zhao, D. Liao, M. Wang, J. Xiang | 2024 | 2024 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD) | https://github.com/drtt438/AEDD | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10580267 |
| 267 | Backdoor Learning: A Survey | Y. Li, Y. Jiang, Z. Li, S. -T. Xia | 2024 | IEEE Transactions on Neural Networks and Learning Systems | https://github.com/THUYimingLi/backdoor-learning-resources | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9802938 |
| 268 | CAFI: News Recommendation with Candidate Perception of Fine-Grained Interaction Information | Y. Li, Z. Yang, X. Li, Z. Li | 2024 | 2024 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD) | https://github.com/liyiweneven/CAFI | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10580786 |
| 269 | CDQKL: Consensus-Based Distributed Quantum Kernel Learning | W. Ma, M. Liu, R. Deng | 2024 | 2024 International Conference on Quantum Communications, Networking, and Computing (QCNC) | https://github.com/Leisurivan/CDOKL | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10628264 |
| 270 | Collaborative Learning of Anomalies with Privacy (CLAP) for Unsupervised Video Anomaly Detection: A New Baseline | A. Al-lahham, M. Z. Zaheer, N. Tastan, K. Nandakumar | 2024 | 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | https://github.com/AnasEmadllICLAP | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10658335 |
| 271 | Data Valuation and Detections in Federated Learning | Wenqian Li, Shuran Fu, Fengrui Zhang, Yan Pang | 2024 | 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | https://github.com/muz1lee/MOTdata | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10656892 |
| 272 | FedTP: Federated Learning by Transformer Personalization | Hongxia Li, Zhongyi Cai, Jingya Wang, Jiangnan Tang, Weiping Ding, Chin-Teng Lin, Ye Shi | 2024 | IEEE Transactions on Neural Networks and Learning Systems | https://github.com/zhyczy/FedTP | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10130784 |
| 273 | Decentralized Landslide Disaster Prediction for Imbalanced and Distributed Data | R. Ozeki, H. Yonekura, H. Rizk, H. Yamaguchi | 2024 | 2024 IEEE International Conference on Pervasive Computing and Communications (PerCom) | https://github.com/mclab-osaka/slidesafe | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10494417 |
| 274 | Deep Class-Incremental Learning From Decentralized Data | X. Zhang, S. Dong, J. Chen, Q. Tian, Y. Gong, X. Hong | 2024 | IEEE Transactions on Neural Networks and Learning Systems | https://github.com/Vision-Intelligence-and-Robots-Group/DCIL | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9932643 |
| 275 | Efficient LWPooling: Rethinking the Wavelet Pooling for Scene Parsing | Y. Yang, L. Jiao, X. Liu, L. Li, F. Liu, S. Yang, X. Zhang | 2024 | IEEE Transactions on Circuits and Systems for Video Technology | https://github.com/yutinyang/LWCNet | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10485451 |
| 276 | FedConv: Enhancing Convolutional Neural Networks for Handling Data Heterogeneity in Federated Learning | Peiran Xu, Zeyu Wang, Jieru Mei, Liangqiong Qu, Alan L. Yuille, Cihang Xie, Yuyin Zhou | 2024 | arXiv | https://github.com/UCSC-VLAA/FedConv | https://doi.org/10.48550/arXiv.2310.04412 |
| 277 | FedDP: Dual Personalization in Federated Medical Image Segmentation | J. Wang, Y. Jin, D. Stoyanov, L. Wang | 2024 | IEEE Transactions on Medical Imaging | https://github.com/jcwang123/PFL-Seg-Trans | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10194959 |
| 278 | FedIOD: Federated Multi-Organ Segmentation From Partial Labels by Exploring Inter-Organ Dependency | Q. Wan, Z. Yan, L. Yu | 2024 | IEEE Journal of Biomedical and Health Informatics | https://github.com/vagabond-healer/FedIOD | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10487890 |
| 279 | FedLAP-DP: Federated Learning by Sharing Differentially Private Loss Approximations | Hui-Po Wang, Dingfan Chen, Raouf Kerkouche, Mario Fritz | 2024 | Proc. Priv. Enhancing Technol. | https://github.com/a514514772/FedLAP-DP | https://doi.org/10.56553/popets-2024-0083 |
| 280 | FedOSS: Federated Open Set Recognition via Inter-Client Discrepancy and Collaboration | M. Zhu, J. Liao, J. Liu, Y. Yuan | 2024 | IEEE Transactions on Medical Imaging | https://github.com/CityU-AIM-Group/FedOSS | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10177875 |
| 281 | Personalized Federated Learning with Adaptive Batchnorm for Healthcare | Wang Lu, Jindong Wang, Yiqiang Chen, Xin Qin, Renjun Xu, Dimitrios Dimitriadis, Tao Qin | 2024 | IEEE Transactions on Big Data | https://github.com/microsoft/personalizedfl | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9780172 |
| 282 | Replica Tree-based Federated Learning using Limited Data | Ramona Ghilea, Islem Rekik | 2023-12-28 | arXiv | https://github.com/basiralab/RepTreeFL | https://doi.org/10.48550/arXiv.2312.17159 |
| 283 | Multimodal Federated Learning with Missing Modality via Prototype Mask and Contrast | Guangyin Bao, Qi Zhang, Duoqian Miao, Zixuan Gong, Liang Hu, Ke Liu, Yang Liu, Chongyang Shi | 2023-12-21 | arXiv | https://github.com/BaoGuangYin/PmcmFL | https://doi.org/10.48550/arXiv.2312.13508 |
| 284 | FedA3I: Annotation Quality-Aware Aggregation for Federated Medical Image Segmentation against Heterogeneous Annotation Noise | Nannan Wu, Zhaobin Sun, Zengqiang Yan, Li Yu | 2023-12-20 | arXiv | https://github.com/wnn2000/FedAAAI | http://arxiv.org/abs/2312.12838v2 |
| 285 | Language-Guided Transformer for Federated Multi-Label Classification | I-Jieh Liu, Ci-Siang Lin, Fu-En Yang, Yu-Chiang Frank Wang | 2023-12-12 | arXiv | https://github.com/Jack24658735/FedLGT | http://arxiv.org/abs/2312.07165v1 |
| 286 | Federated Full-Parameter Tuning of Billion-Sized Language Models with Communication Cost under 18 Kilobytes | Zhen Qin, Daoyuan Chen, Bingchen Qian, Bolin Ding, Yaliang Li, Shuiguang Deng | 2023-12-11 | arXiv | https://github.com/alibaba/FederatedScope/tree/FedKSeed | http://arxiv.org/abs/2312.06353v5 |
| 287 | Fed-urlBERT: Client-side Lightweight Federated Transformers for URL Threat Analysis | Yujie Li, Yanbin Wang, Haitao Xu, Zhenhao Guo, Fan Zhang, Ruitong Liu, Wenrui Ma | 2023-12-06 | arXiv | https://github.com/Davidup1/FedURLBERT | http://arxiv.org/abs/2312.03636v1 |
| 288 | FedECA: A Federated External Control Arm Method for Causal Inference with Time-To-Event Data in Distributed Settings | Jean Ogier du Terrail, Quentin Klopfenstein, Honghao Li, Imke Mayer, Nicolas Loiseau, Mohammad Hallal, Félix Balazard, Mathieu Andreux | 2023-11-28 | arXiv | https://github.com/owkin/fedeca | http://arxiv.org/abs/2311.16984v2 |
| 289 | VeryFL: A Verify Federated Learning Framework Embedded with Blockchain | Yihao Li, Yanyi Lai, Chuan Chen, Zibin Zheng | 2023-11-27 | arXiv | https://github.com/GTMLLab/VeryFL | https://doi.org/10.48550/arXiv.2311.15617 |
| 290 | Eliminating Domain Bias for Federated Learning in Representation Space | Jianqing Zhang, Yang Hua, Jian Cao, Hao Wang, Tao Song, Zhengui Xue, Ruhui Ma, Haibing Guan | 2023-11-25 | NeurIPS | https://github.com/TsingZ0/DBE | http://papers.nips.cc/paper_files/paper/2023/hash/2e0d3c6ad1a4d85bef3cfe63af58bc76-Abstract-Conference.html |
| 291 | FedRA: A Random Allocation Strategy for Federated Tuning to Unleash the Power of Heterogeneous Clients | Shangchao Su, Bin Li, Xiangyang Xue | 2023-11-19 | arXiv | https://github.com/leondada/FedRA | http://arxiv.org/abs/2311.11227v2 |
| 292 | Tunable Soft Prompts are Messengers in Federated Learning | Chenhe Dong, Yuexiang Xie, Bolin Ding, Ying Shen, Yaliang Li | 2023-11-12 | EMNLP | https://github.com/alibaba/FederatedScope/tree/fedsp/federatedscope/nlp/fedsp | https://doi.org/10.18653/v1/2023.findings-emnlp.976 |
| 293 | Heterogeneous federated collaborative filtering using FAIR: Federated Averaging in Random Subspaces | Aditya Desai, Benjamin Meisburger, Zichang Liu, Anshumali Shrivastava | 2023-11-03 | arXiv | https://github.com/apd10/FLCF | http://arxiv.org/abs/2311.01722v1 |
| 294 | Consumer-Centric Internet of Medical Things for Cyborg Applications Based on Federated Reinforcement Learning | Prayag Tiwari, Abdullah Lakhan, Rutvij H. Jhaveri, Tor-Morten Grønli | 2023-11-01 | IEEE Transactions on Consumer Electronics | https://github.com/prayagtiwari/CIoMT | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10040613 |
| 295 | Federated Learning With Taskonomy for Non-IID Data | Hadi Jamali Rad, Mohammad Abdizadeh, Attila Szabó | 2023-11-01 | IEEE Transactions on Neural Networks and Learning Systems | https://github.com/hjraad/FLT/ | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9739132 |
| 296 | Modeling Global Distribution for Federated Learning with Label Distribution Skew | Tao Sheng, Chengchao Shen, Yuan Liu, Yeyu Ou, Zhe Qu, Yixiong Liang, Jianxin Wang | 2023-11-01 | arXiv | https://github.com/Sheng-T/FedMGD | https://doi.org/10.48550/arXiv.2212.08883 |
| 297 | A Survey of Federated Unlearning: A Taxonomy, Challenges and Future Directions | Yang Zhao, Jiaxi Yang, Yiling Tao, Lixu Wang, Xiaoxiao Li, Dusit Niyato | 2023-10-30 | arXiv | https://github.com/abbottyanginchina/Awesome-Federated-Unlearning | http://arxiv.org/abs/2310.19218v3 |
| 298 | Adaptive Test-Time Personalization for Federated Learning | Wenxuan Bao, Tianxin Wei, Haohan Wang, Jingrui He | 2023-10-28 | NeurIPS | https://github.com/baowenxuan/ATP | http://papers.nips.cc/paper_files/paper/2023/hash/f555b62384279b98732204cb1a670a23-Abstract-Conference.html |
| 299 | Cross-Silo Prototypical Calibration for Federated Learning with Non-IID Data | Zhuang Qi, Lei Meng, Zitan Chen, Han Hu, Hui Lin, Xiangxu Meng | 2023-10-26 | ACM Multimedia | https://github.com/qizhuang-qz/FedCSPC | https://doi.org/10.1145/3581783.3612481 |
| 300 | Federated Learning of Large Language Models with Parameter-Efficient Prompt Tuning and Adaptive Optimization | Tianshi Che, Ji Liu, Yang Zhou, Jiaxiang Ren, Jiwen Zhou, Victor S. Sheng, Huaiyu Dai, Dejing Dou | 2023-10-23 | EMNLP | https://github.com/llm-eff/FedPepTAO | https://doi.org/10.18653/v1/2023.emnlp-main.488 |
| 301 | Handling Data Heterogeneity via Architectural Design for Federated Visual Recognition | Sara Pieri, Jose Renato Restom, Samuel Horvath, Hisham Cholakkal | 2023-10-23 | arXiv | https://github.com/sarapieri/fed_het | http://arxiv.org/abs/2310.15165v1 |
| 302 | Whole-brain radiomics for clustered federated personalization in brain tumor segmentation | Matthis Manthe, Stefan Duffner, Carole Lartizien | 2023-10-17 | MIDL 2023 Poster | https://github.com/MatthisManthe/radiomics_CFFL | http://arxiv.org/abs/2310.11480v1 |
| 303 | FATE-LLM: A Industrial Grade Federated Learning Framework for Large Language Models | Tao Fan, Yan Kang, Guoqiang Ma, Weijing Chen, Wenbin Wei, Lixin Fan, Qiang Yang | 2023-10-16 | arXiv | https://github.com/FederatedAI/FATE-LLM | https://doi.org/10.48550/arXiv.2310.10049 |
| 304 | FedNAR: Federated Optimization with Normalized Annealing Regularization | Junbo Li, Ang Li, Chong Tian, Qirong Ho, Eric P. Xing, Hongyi Wang | 2023-10-04 | Thirty-seventh Conference on Neural Information Processing Systems, 2023 | https://github.com/ljb121002/fednar | http://arxiv.org/abs/2310.03163v1 |
| 305 | FedAWARE: Maximizing Gradient Diversity for Heterogeneous Federated Server-side Optimization | Dun Zeng, Zenglin Xu, Yu Pan, Qifan Wang, Xiaoying Tang | 2023-10-04 | arXiv | https://github.com/dunzeng/FedAWARE | http://arxiv.org/abs/2310.02702v3 |
| 306 | FedAIoT: A Federated Learning Benchmark for Artificial Intelligence of Things | Samiul Alam, Tuo Zhang, Tiantian Feng, Hui Shen, Zhichao Cao, Dong Zhao, JeongGil Ko, Kiran Somasundaram, Shrikanth S. Narayanan, Salman Avestimehr, Mi Zhang | 2023-09-29 | arXiv | https://github.com/AIoT-MLSys-Lab/FedAIoT | https://doi.org/10.48550/arXiv.2310.00109 |
| 307 | FedDrive v2: an Analysis of the Impact of Label Skewness in Federated Semantic Segmentation for Autonomous Driving | Eros Fanì, Marco Ciccone, Barbara Caputo | 2023-09-23 | arXiv | https://feddrive.github.io | http://arxiv.org/abs/2309.13336v2 |
| 308 | FedJudge: Federated Legal Large Language Model | Linan Yue, Qi Liu, Yichao Du, Weibo Gao, Ye Liu, Fangzhou Yao | 2023-09-15 | arXiv | https://github.com/yuelinan/FedJudge | http://arxiv.org/abs/2309.08173v3 |
| 309 | FedDIP: Federated Learning with Extreme Dynamic Pruning and Incremental Regularization | Qianyu Long, Christos Anagnostopoulos, Shameem Puthiya Parambath, Daning Bi | 2023-09-13 | ICDM | https://github.com/EricLoong/feddip | https://doi.org/10.1109/ICDM58522.2023.00146 |
| 310 | Mitigating Adversarial Attacks in Federated Learning with Trusted Execution Environments | Simon Queyrut, Valerio Schiavoni, Pascal Felber | 2023-09-13 | 2023 IEEE 43rd International Conference on Distributed Computing Systems (ICDCS) | https://github.com/queyrusi/Pelta | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10272529 |
| 311 | Share Your Representation Only: Guaranteed Improvement of the Privacy-Utility Tradeoff in Federated Learning | Zebang Shen, Jiayuan Ye, Anmin Kang, Hamed Hassani, Reza Shokri | 2023-09-11 | ICLR | https://github.com/shenzebang/CENTAUR-Privacy-Federated-Representation-Learning | https://openreview.net/pdf?id=oJpVVGXu9i |
| 312 | FedAUX: Leveraging Unlabeled Auxiliary Data in Federated Learning | Felix Sattler, Tim Korjakow, Roman Rischke, Wojciech Samek | 2023-09-01 | IEEE Transactions on Neural Networks and Learning Systems | https://github.com/fedl-repo/fedaux | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9632275 |
| 313 | MrTF: model refinery for transductive federated learning | Xin-Chun Li, Yang Yang, De-Chuan Zhan | 2023-09-01 | Data Min. Knowl. Discov. | https://github.com/lxcnju/MrTF | https://doi.org/10.1007/s10618-023-00946-4 |
| 314 | CEFHRI: A Communication Efficient Federated Learning Framework for Recognizing Industrial Human-Robot Interaction | Umar Khalid, Hasan Iqbal, Saeed Vahidian, Jing Hua, Chen Chen | 2023-08-29 | IROS | https://github.com/umarkhalidAI/CEFHRI-Efficient-Federated-Learning | https://doi.org/10.1109/IROS55552.2023.10341467 |
| 315 | Generalizable Learning Reconstruction for Accelerating MR Imaging via Federated Neural Architecture Search | Ruoyou Wu, Cheng Li, Juan Zou, Shanshan Wang | 2023-08-27 | arXiv | https://github.com/ternencewu123/GAutoMRI | http://arxiv.org/abs/2308.13995v1 |
| 316 | Federated Learning on Patient Data for Privacy-Protecting Polycystic Ovary Syndrome Treatment | Lucia Morris, Tori Qiu, Nikhil Raghuraman | 2023-08-22 | arXiv | https://github.com/toriqiu/fl-pcos | https://doi.org/10.48550/arXiv.2308.11220 |
| 317 | FedSIS: Federated Split Learning with Intermediate Representation Sampling for Privacy-preserving Generalized Face Presentation Attack Detection | Naif Alkhunaizi, Koushik Srivatsan, Faris Almalik, Ibrahim Almakky, Karthik Nandakumar | 2023-08-20 | IJCB | https://github.com/Naiftt/FedSIS | https://doi.org/10.1109/IJCB57857.2023.10448785 |
| 318 | FedPop: Federated Population-based Hyperparameter Tuning | Haokun Chen, Denis Krompass, Jindong Gu, Volker Tresp | 2023-08-16 | arXiv | https://github.com/HaokunChen245/FedPop | http://arxiv.org/abs/2308.08634v2 |
| 319 | Federated Learning Hyperparameter Tuning From a System Perspective | Huanle Zhang, Lei Fu, Mi Zhang, Pengfei Hu, Xiuzhen Cheng, Prasant Mohapatra, Xin Liu | 2023-08-15 | IEEE Internet of Things Journal | https://github.com/DataSysTech/FedTune | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10064046 |
| 320 | ConDistFL: Conditional Distillation for Federated Learning from Partially Annotated Data | Pochuan Wang, Chen Shen, Weichung Wang, Masahiro Oda, Chiou-Shann Fuh, Kensaku Mori, Holger R. Roth | 2023-08-08 | ISIC/Care-AI/MedAGI/DeCaF@MICCAI | https://github.com/NVIDIA/NVFlare/tree/dev/research/condist-fl | https://doi.org/10.1007/978-3-031-47401-9_30 |
| 321 | FedMultimodal: A Benchmark for Multimodal Federated Learning | Tiantian Feng, Digbalay Bose, Tuo Zhang, Rajat Hebbar, Anil Ramakrishna, Rahul Gupta, Mi Zhang, Salman Avestimehr, Shrikanth Narayanan | 2023-08-06 | KDD '23: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining | https://github.com/usc-sail/fed-multimodal | https://dl.acm.org/doi/10.1145/3580305.3599825 |
| 322 | Revisiting Personalized Federated Learning: Robustness Against Backdoor Attacks | Zeyu Qin, Liuyi Yao, Daoyuan Chen, Yaliang Li, Bolin Ding, Minhao Cheng | 2023-08-06 | KDD | https://github.com/alibaba/FederatedScope/tree/backdoor-bench | https://doi.org/10.1145/3580305.3599898 |
| 323 | FedCP: Separating Feature Information for Personalized Federated Learning via Conditional Policy | Jianqing Zhang, Yang Hua, Hao Wang, Tao Song, Zhengui Xue, Ruhui Ma, Haibing Guan | 2023-08-06 | KDD '23: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining | https://github.com/TsingZ0/FedCP | https://dl.acm.org/doi/10.1145/3580305.3599345 |
| 324 | PoE: Poisoning Enhancement Through Label Smoothing in Federated Learning | Haibin Zheng, Tao Liu, Rongchang Li, Jinyin Chen | 2023-08-01 | IEEE Transactions on Circuits and Systems II: Express Briefs | https://github.com/Leon022/poisoning_enhancement | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10061375 |
| 325 | You Can Backdoor Personalized Federated Learning | Tiandi Ye, Cen Chen, Yinggui Wang, Xiang Li, Ming Gao | 2023-07-29 | arXiv | https://github.com/BapFL/code | https://doi.org/10.48550/arXiv.2307.15971 |
| 326 | Federated Model Aggregation via Self-Supervised Priors for Highly Imbalanced Medical Image Classification | Marawan Elbatel, Hualiang Wang, Robert Martí, Huazhu Fu, Xiaomeng Li | 2023-07-27 | arXiv | https://github.com/xmed-lab/Fed-MAS | http://arxiv.org/abs/2307.14959v1 |
| 327 | Client-Level Differential Privacy via Adaptive Intermediary in Federated Medical Imaging | Meirui Jiang, Yuan Zhong, Anjie Le, Xiaoxiao Li, Qi Dou | 2023-07-24 | arXiv | https://github.com/med-air/Client-DP-FL | http://arxiv.org/abs/2307.12542v2 |
| 328 | FedSoup: Improving Generalization and Personalization in Federated Learning via Selective Model Interpolation | Minghui Chen, Meirui Jiang, Qi Dou, Zehua Wang, Xiaoxiao Li | 2023-07-20 | MICCAI | https://github.com/ubc-tea/FedSoup | https://doi.org/10.1007/978-3-031-43895-0_30 |
| 329 | Towards Federated Foundation Models: Scalable Dataset Pipelines for Group-Structured Learning | Zachary Charles, Nicole Mitchell, Krishna Pillutla, Michael Reneer, Zachary Garrett | 2023-07-18 | NeurIPS | https://github.com/google-research/dataset_grouper | http://papers.nips.cc/paper_files/paper/2023/hash/662bb9c4dcc96aeaac8e7cd3fc6a0add-Abstract-Datasets_and_Benchmarks.html |
| 330 | Benchmarking Algorithms for Federated Domain Generalization | Ruqi Bai, Saurabh Bagchi, David I. Inouye | 2023-07-11 | Submitted to ICLR 2023 | https://github.com/inouye-lab/FedDG_Benchmark | http://arxiv.org/abs/2307.04942v2 |
| 331 | Towards Open Federated Learning Platforms: Survey and Vision from Technical and Legal Perspectives | Moming Duan, Qinbin Li, Linshan Jiang, Bingsheng He | 2023-07-05 | arXiv | https://github.com/morningD/Towards-Open-Federated-Learning-Platforms-Survey/blob/main/TKDE-Tex/APPENDIX.pdf | https://doi.org/10.48550/arXiv.2307.02140 |
| 332 | One-shot Federated Learning without Server-side Training | Shangchao Su, Bin Li, Xiangyang Xue | 2023-07-01 | arXiv | https://github.com/FudanVI/MAEcho | https://doi.org/10.48550/arXiv.2204.12493 |
| 333 | Specificity-Preserving Federated Learning for MR Image Reconstruction | Chun-Mei Feng, Yunlu Yan, Shanshan Wang, Yong Xu, Ling Shao, Huazhu Fu | 2023-07-01 | IEEE Transactions on Medical Imaging | https://github.com/chunmeifeng/FedMRI | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9868072 |
| 334 | Semi-Federated Learning for Collaborative Intelligence in Massive IoT Networks | Wanli Ni, Jingheng Zheng, Hui Tian | 2023-07-01 | IEEE Internet of Things Journal | https://github.com/niwanli/SemiFL_IoT | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10064038 |
| 335 | Do Gradient Inversion Attacks Make Federated Learning Unsafe? | Ali Hatamizadeh, Hongxu Yin, Pavlo Molchanov, Andriy Myronenko, Wenqi Li, Prerna Dogra, Andrew Feng, Mona G. Flores, Jan Kautz, Daguang Xu, Holger R. Roth | 2023-07-01 | IEEE Transactions on Medical Imaging | https://nvidia.github.io/NVFlare/research/quantifying-data-leakage | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10025466 |
| 336 | Label-Efficient Self-Supervised Federated Learning for Tackling Data Heterogeneity in Medical Imaging | Rui Yan, Liangqiong Qu, Qingyue Wei, Shih-Cheng Huang, Liyue Shen, Daniel L. Rubin, Lei Xing, Yuyin Zhou | 2023-07-01 | IEEE Transactions on Medical Imaging | https://github.com/rui-yan/SSL-FL | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10004993 |
| 337 | FedMix: Mixed Supervised Federated Learning for Medical Image Segmentation | Jeffry Wicaksana, Zengqiang Yan, Dong Zhang, Xijie Huang, Huimin Wu, Xin Yang, Kwang-Ting Cheng | 2023-07-01 | IEEE Transactions on Medical Imaging | https://github.com/Jwicaksana/FedMix | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10004567 |
| 338 | Improving Federated Aggregation with Deep Unfolding Networks | Shanika I Nanayakkara, Shiva Raj Pokhrel, Gang Li | 2023-06-30 | arXiv | https://github.com/shanikairoshi/Improved_DUN_basedFL_Aggregation | http://arxiv.org/abs/2306.17362v1 |
| 339 | DPAUC: Differentially Private AUC Computation in Federated Learning | Jiankai Sun, Xin Yang, Yuanshun Yao, Junyuan Xie, Di Wu, Chong Wang | 2023-06-27 | arXiv | https://github.com/bytedance/fedlearner/tree/master/example/privacy/DPAUC | https://doi.org/10.48550/arXiv.2208.12294 |
| 340 | Efficient Distribution Similarity Identification in Clustered Federated Learning via Principal Angles Between Client Data Subspaces | Saeed Vahidian, Mahdi Morafah, Weijia Wang, Vyacheslav Kungurtsev, Chen Chen, Mubarak Shah, Bill Lin | 2023-06-27 | arXiv | https://github.com/MMorafah/PACFL | https://doi.org/10.48550/arXiv.2209.10526 |
| 341 | FeSViBS: Federated Split Learning of Vision Transformer with Block Sampling | Faris Almalik, Naif Alkhunaizi, Ibrahim Almakky, Karthik Nandakumar | 2023-06-26 | MICCAI | https://github.com/faresmalik/FeSViBS | https://doi.org/10.1007/978-3-031-43895-0_33 |
| 342 | Personalized Federated Learning with Feature Alignment and Classifier Collaboration | Jian Xu, Xinyi Tong, Shao-Lun Huang | 2023-06-20 | ICLR | https://github.com/JianXu95/FedPAC | https://openreview.net/pdf?id=SXZr8aDKia |
| 343 | FedNoisy: Federated Noisy Label Learning Benchmark | Siqi Liang, Jintao Huang, Dun Zeng, Junyuan Hong, Jiayu Zhou, Zenglin Xu | 2023-06-20 | arXiv | https://github.com/SMILELab-FL/FedNoisy | https://doi.org/10.48550/arXiv.2306.11650 |
| 344 | Bkd-FedGNN: A Benchmark for Classification Backdoor Attacks on Federated Graph Neural Network | Fan Liu, Siqi Lai, Yansong Ning, Hao Liu | 2023-06-17 | arXiv | https://github.com/usail-hkust/BkdFedGCN | http://arxiv.org/abs/2306.10351v1 |
| 345 | A Client-Server Deep Federated Learning for Cross-Domain Surgical Image Segmentation | Ronast Subedi, Rebati Raman Gaire, Sharib Ali, Anh Nguyen, Danail Stoyanov, Binod Bhattarai | 2023-06-14 | DEMI@MICCAI | https://github.com/thetna/distributed-da | https://doi.org/10.1007/978-3-031-44992-5_3 |
| 346 | Improving Fairness in AI Models on Electronic Health Records: The Case for Federated Learning Methods | Raphael Poulain, Mirza Farhan Bin Tarek, Rahmatollah Beheshti | 2023-06-12 | FAccT | https://github.com/healthylaife/FairFedAvg | https://doi.org/10.1145/3593013.3594102 |
| 347 | GPT-FL: Generative Pre-trained Model-Assisted Federated Learning | Tuo Zhang, Tiantian Feng, Samiul Alam, Dimitrios Dimitriadis, Sunwoo Lee, Mi Zhang, Shrikanth S. Narayanan, Salman Avestimehr | 2023-06-03 | arXiv | https://github.com/AvestimehrResearchGroup/GPT-FL | https://doi.org/10.48550/arXiv.2306.02210 |
| 348 | Fed-HANet: Federated Visual Grasping Learning for Human Robot Handovers | Ching-I Huang, Yu-Yen Huang, Jie-Xin Liu, Yu-Ting Ko, Hsueh-Cheng Wang, Kuang-Hsing Chiang, Lap-Fai Yu | 2023-06-01 | IEEE Robotics and Automation Letters | https://arg-nctu.github.io/projects/fed-hanet.html | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10109097 |
| 349 | FedRadar: Federated Multi-Task Transfer Learning for Radar-Based Internet of Medical Things | Xikang Jiang, Jinhui Zhang, Lin Zhang | 2023-06-01 | IEEE Transactions on Network and Service Management | https://github.com/bupt-uwb/FedRadar | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10138687 |
| 350 | Non-IID quantum federated learning with one-shot communication complexity | Haimeng Zhao | 2023-06-01 | Quantum Mach. Intell. | https://github.com/JasonZHM/quantum-fed-infer | https://doi.org/10.1007/s42484-022-00091-z |
| 351 | Surrogate Model Extension (SME): A Fast and Accurate Weight Update Attack on Federated Learning | Junyi Zhu, Ruicong Yao, Matthew B. Blaschko | 2023-05-31 | ICML | https://github.com/JunyiZhu-AI/surrogate_model_extension | https://proceedings.mlr.press/v202/zhu23m.html |
| 352 | FedDisco: Federated Learning with Discrepancy-Aware Collaboration | Rui Ye, Mingkai Xu, Jianyu Wang, Chenxin Xu, Siheng Chen, Yanfeng Wang | 2023-05-30 | ICML | https://github.com/MediaBrain-SJTU/FedDisco | https://proceedings.mlr.press/v202/ye23f.html |
| 353 | Global Layers: Non-IID Tabular Federated Learning | Yazan Obeidi | 2023-05-29 | arXiv | https://github.com/transferFL/gl/ | https://doi.org/10.48550/arXiv.2305.19290 |
| 354 | Federated Conformal Predictors for Distributed Uncertainty Quantification | Charles Lu, Yaodong Yu, Sai Praneeth Karimireddy, Michael I. Jordan, Ramesh Raskar | 2023-05-27 | arXiv | https://github.com/clu5/federated-conformal | http://arxiv.org/abs/2305.17564v2 |
| 355 | FedHC: A Scalable Federated Learning Framework for Heterogeneous and Resource-Constrained Clients | Min Zhang, Fuxun Yu, Yongbo Yu, Minjia Zhang, Ang Li, Xiang Chen | 2023-05-25 | arXiv | https://github.com/if-lab-repository/FedHC | https://doi.org/10.48550/arXiv.2305.15668 |
| 356 | Federated Learning of Medical Concepts Embedding using BEHRT | Ofir Ben Shoham, Nadav Rappoport | 2023-05-22 | arXiv | https://github.com/nadavlab/FederatedBEHRT | https://doi.org/10.48550/arXiv.2305.13052 |
| 357 | Confidence-Aware Personalized Federated Learning via Variational Expectation Maximization | Junyi Zhu, Xingchen Ma, Matthew B. Blaschko | 2023-05-21 | CVPR | https://github.com/JunyiZhu-AI/confidence_aware_PFL | https://doi.org/10.1109/CVPR52729.2023.02351 |
| 358 | FedHGN: A Federated Framework for Heterogeneous Graph Neural Networks | Xinyu Fu, Irwin King | 2023-05-16 | arXiv | https://github.com/cynricfu/FedHGN | http://arxiv.org/abs/2305.09729v1 |
| 359 | Securing Distributed SGD Against Gradient Leakage Threats | Wenqi Wei, Ling Liu, Jingya Zhou, Ka-Ho Chow, Yanzhao Wu | 2023-05-10 | IEEE Transactions on Parallel and Distributed Systems | https://github.com/git-disl/Fed-alphaCDP | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10119168 |
| 360 | Gradient Leakage Defense with Key-Lock Module for Federated Learning | Hanchi Ren, Jingjing Deng, Xianghua Xie, Xiaoke Ma, Jianfeng Ma | 2023-05-06 | arXiv | https://github.com/Rand2AI/FedKL | https://doi.org/10.48550/arXiv.2305.04095 |
| 361 | FedFormer: Contextual Federation with Attention in Reinforcement Learning | Liam Hebert, Lukasz Golab, Pascal Poupart, Robin Cohen | 2023-05 | AAMAS '23: Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems | https://github.com/liamhebert/FedFormer | https://dl.acm.org/doi/10.5555/3545946.3598716 |
| 362 | Denial-of-Service or Fine-Grained Control: Towards Flexible Model Poisoning Attacks on Federated Learning | Hangtao Zhang, Zeming Yao, Leo Yu Zhang, Shengshan Hu, Chao Chen, Alan Wee-Chung Liew, Zhetao Li | 2023-04-21 | IJCAI | https://github.com/ZhangHangTao/Poisoning-Attack-on-FL | https://doi.org/10.24963/ijcai.2023/508 |
| 363 | Scale Federated Learning for Label Set Mismatch in Medical Image Classification | Zhipeng Deng, Luyang Luo, Hao Chen | 2023-04-14 | MICCAI | https://github.com/dzp2095/FedLSM | https://doi.org/10.1007/978-3-031-43898-1_12 |
| 364 | Unifying and Personalizing Weakly-supervised Federated Medical Image Segmentation via Adaptive Representation and Aggregation | Li Lin, Jiewei Wu, Yixiang Liu, Kenneth K. Y. Wong, Xiaoying Tang | 2023-04-12 | arXiv | https://github.com/llmir/FedICRA | http://arxiv.org/abs/2304.05635v1 |
| 365 | Federated Incremental Semantic Segmentation | Jiahua Dong, Duzhen Zhang, Yang Cong, Wei Cong, Henghui Ding, Dengxin Dai | 2023-04-10 | arXiv | https://github.com/JiahuaDong/FISS | http://arxiv.org/abs/2304.04620v1 |
| 366 | Asynchronous Federated Continual Learning | Donald Shenaj, Marco Toldo, Alberto Rigon, Pietro Zanuttigh | 2023-04-07 | CVPR Workshops | https://github.com/LTTM/FedSpace | https://doi.org/10.1109/CVPRW59228.2023.00534 |
| 367 | Generalizing intrusion detection for heterogeneous networks: A stacked-unsupervised federated learning approach | Gustavo de Carvalho Bertoli, Lourenço Alves Pereira Júnior, Aldri Luiz dos Santos, Osamu Saotome | 2023-04-01 | arXiv | https://github.com/c2dc/fl-unsup-nids | https://doi.org/10.48550/arXiv.2209.00721 |
| 368 | Graph-Fraudster: Adversarial Attacks on Graph Neural Network-Based Vertical Federated Learning | Jinyin Chen, Guohan Huang, Haibin Zheng, Shanqing Yu, Wenrong Jiang, Chen Cui | 2023-04-01 | IEEE Transactions on Computational Social Systems | https://github.com/hgh0545/Graph-Fraudster | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9745270 |
| 369 | Privacy vs. Efficiency: Achieving Both Through Adaptive Hierarchical Federated Learning | Yeting Guo, Fang Liu, Tongqing Zhou, Zhiping Cai, Nong Xiao | 2023-04-01 | IEEE Transactions on Parallel and Distributed Systems | https://github.com/Guoyeting/AHFL | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10043027 |
| 370 | Communication-Efficient Vertical Federated Learning with Limited Overlapping Samples | Jingwei Sun, Ziyue Xu, Dong Yang, Vishwesh Nath, Wenqi Li, Can Zhao, Daguang Xu, Yiran Chen, Holger R. Roth | 2023-03-28 | ICCV | https://nvidia.github.io/NVFlare/research/one-shot-vfl | https://doi.org/10.1109/ICCV51070.2023.00480 |
| 371 | Personalized Federated Learning on Long-Tailed Data via Adversarial Feature Augmentation | Yang Lu, Pinxin Qian, Gang Huang, Hanzi Wang | 2023-03-27 | ICASSP | https://github.com/pxqian/FedAFA | https://doi.org/10.1109/ICASSP49357.2023.10097083 |
| 372 | Dealing with Heterogeneous 3d Mr Knee Images: A Federated Few-Shot Learning Method with Dual Knowledge Distillation | Xiaoxiao He, Chaowei Tan, Bo Liu, Liping Si, Weiwu Yao, Liang Zhao, Di Liu, Qilong Zhangli, Qi Chang, Kang Li, Dimitris N. Metaxas | 2023-03-25 | 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI) | https://github.com/hexiaoxiao-cs/fedml-knee | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10230679 |
| 373 | STDLens: Model Hijacking-Resilient Federated Learning for Object Detection | Ka Ho Chow, Ling Liu, Wenqi Wei, Fatih Ilhan, Yanzhao Wu | 2023-03-21 | CVPR | https://github.com/git-disl/STDLens | https://doi.org/10.1109/CVPR52729.2023.01568 |
| 374 | Make Landscape Flatter in Differentially Private Federated Learning | Yifan Shi, Yingqi Liu, Kang Wei, Li Shen, Xueqian Wang, Dacheng Tao | 2023-03-20 | CVPR | https://github.com/YMJS-Irfan/DP-FedSAM | https://doi.org/10.1109/CVPR52729.2023.02352 |
| 375 | Knowledge-Enhanced Semi-Supervised Federated Learning for Aggregating Heterogeneous Lightweight Clients in IoT | Jiaqi Wang, Shenglai Zeng, Zewei Long, Yaqing Wang, Houping Xiao, Fenglong Ma | 2023-03-05 | SDM | https://github.com/JackqqWang/pfedknow/tree/master | https://doi.org/10.1137/1.9781611977653.ch56 |
| 376 | Combating Exacerbated Heterogeneity for Robust Models in Federated Learning | Jianing Zhu, Jiangchao Yao, Tongliang Liu, Quanming Yao, Jianliang Xu, Bo Han | 2023-03-01 | ICLR | https://github.com/ZFancy/SFAT | https://openreview.net/pdf?id=eKllxpLOOm |
| 377 | FedCLIP: Fast Generalization and Personalization for CLIP in Federated Learning | Wang Lu, Xixu Hu, Jindong Wang, Xing Xie | 2023-02-27 | IEEE Data Eng. Bull. | https://github.com/microsoft/PersonalizedFL | http://sites.computer.org/debull/A23mar/p52.pdf |
| 378 | Better Generative Replay for Continual Federated Learning | Daiqing Qi, Handong Zhao, Sheng Li | 2023-02-25 | ICLR | https://github.com/daiqing98/FedCIL | https://openreview.net/pdf?id=cRxYWKiTan |
| 379 | Fusion of Global and Local Knowledge for Personalized Federated Learning | Tiansheng Huang, Li Shen, Yan Sun, Weiwei Lin, Dacheng Tao | 2023-02-21 | Trans. Mach. Learn. Res. | https://github.com/huangtiansheng/fedslr | https://openreview.net/forum?id=QtrjqVIZna |
| 380 | EPISODE: Episodic Gradient Clipping with Periodic Resampled Corrections for Federated Learning with Heterogeneous Data | Michael Crawshaw, Yajie Bao, Mingrui Liu | 2023-02-14 | ICLR | https://github.com/MingruiLiu-ML-Lab/episode | https://openreview.net/pdf?id=ytZIYmztET |
| 381 | XFL: A High Performace, Lightweighted Federated Learning Framework | Hong Wang, Yuanzhi Zhou, Chi Zhang, Chen Peng, Mingxia Huang, Yi Liu, Lintao Zhang | 2023-02-10 | arXiv | https://github.com/paritybit-ai/XFL | https://doi.org/10.48550/arXiv.2302.05076 |
| 382 | A Privacy-Preserving Hybrid Federated Learning Framework for Financial Crime Detection | Haobo Zhang, Junyuan Hong, Fan Dong, Steve Drew, Liangjie Xue, Jiayu Zhou | 2023-02-07 | arXiv | https://github.com/illidanlab/HyFL | https://doi.org/10.48550/arXiv.2302.03654 |
| 383 | Memory-aware curriculum federated learning for breast cancer classification | Amelia Jiménez-Sánchez, Mickael Tardy, Miguel Ángel González Ballester, Diana Mateus, Gemma Piella | 2023-02-01 | arXiv | https://github.com/ameliajimenez/curriculum-federated-learning | https://arxiv.org/abs/2107.02504 |
| 384 | FedFA: Federated Feature Augmentation | Tianfei Zhou, Ender Konukoglu | 2023-01-30 | arXiv | https://github.com/tfzhou/FedFA | http://arxiv.org/abs/2301.12995v1 |
| 385 | Regularized Weight Aggregation in Networked Federated Learning for Glioblastoma Segmentation | Muhammad Irfan Khan, Mohammad Ayyaz Azeem, Esa Alhoniemi, Elina Kontio, Suleiman A. Khan, Mojtaba Jafaritadi | 2023-01-30 | BrainLes@MICCAI | https://github.com/dskhanirfan/FeTS2022 | https://doi.org/10.1007/978-3-031-44153-0_12 |
| 386 | Does Federated Learning Really Need Backpropagation? | Haozhe Feng, Tianyu Pang, Chao Du, Wei Chen, Shuicheng Yan, Min Lin | 2023-01-28 | arXiv | https://github.com/FengHZ/BAFFLE | https://doi.org/10.48550/arXiv.2301.12195 |
| 387 | Personalized Federated Learning with Local Optimization Models | Shenhai Zheng, Haihan Xu, Peng Han, Yuanyuan Li, Yufei Chen, Qing Chen | 2023-01-01 | 2023 IEEE 29th International Conference on Parallel and Distributed Systems (ICPADS) | https://github.com/LilRind/pFedLO | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10476205 |
| 388 | GRACE: A Generalized and Personalized Federated Learning Method for Medical Imaging | Ruipeng Zhang, Ziqing Fan, Qinwei Xu, Jiangchao Yao, Ya Zhang, Yanfeng Wang | 2023-01-01 | MICCAI | https://github.com/MediaBrain-SJTU/GPFL-GRACE | https://doi.org/10.1007/978-3-031-43898-1_2 |
| 389 | Hypernetwork-Based Physics-Driven Personalized Federated Learning for CT Imaging | Z. Yang, W. Xia, Z. Lu, Y. Chen, X. Li, Y. Zhang | 2023-01-01 | IEEE Transactions on Neural Networks and Learning Systems | https://github.com/Zi-YuanYang/HyperFed | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10361833 |
| 390 | Knowledge-Aware Federated Active Learning with Non-IID Data | Yu-Tong Cao, Jingya Wang, Ye Shi, Baosheng Yu, Dacheng Tao | 2023-01-01 | 2023 IEEE/CVF International Conference on Computer Vision (ICCV) | https://github.com/ycao5602/KAFAL | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10378423 |
| 391 | Learning Across Domains and Devices: Style-Driven Source-Free Domain Adaptation in Clustered Federated Learning | Donald Shenaj, Eros Fanì, Marco Toldo, Debora Caldarola, Antonio Tavera, Umberto Michieli, Marco Ciccone, Pietro Zanuttigh, Barbara Caputo | 2023-01-01 | 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) | https://github.com/Erosinho13/LADD | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10030428 |
| 392 | One-Shot Federated Learning on Medical Data Using Knowledge Distillation with Image Synthesis and Client Model Adaptation | Myeongkyun Kang, Philip Chikontwe, Soopil Kim, Kyong Hwan Jin, Ehsan Adeli-Mosabbeb, Kilian M. Pohl, Sanghyun Park | 2023-01-01 | MICCAI | https://github.com/myeongkyunkang/FedISCA | https://doi.org/10.1007/978-3-031-43895-0_49 |
| 393 | OpenFed: A Comprehensive and Versatile Open-Source Federated Learning Framework | Dengsheng Chen, Vince Junkai Tan, Zhilin Lu, Enhua Wu, Jie Hu | 2023-01-01 | 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) | https://github.com/FederalLab/OpenFed | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10208573 |
| 394 | PGFed: Personalize Each Client's Global Objective for Federated Learning | Jun Luo, Matías Mendieta, Chen Chen, Shandong Wu | 2023-01-01 | arXiv | https://github.com/ljaiverson/pgfed | https://doi.org/10.48550/arXiv.2212.01448 |
| 395 | Private Non-Convex Federated Learning Without a Trusted Server | Andrew Lowy, Ali Ghafelebashi, Meisam Razaviyayn | 2023-01-01 | arXiv | https://github.com/ghafeleb/Private-NonConvex-Federated-Learning-Without-a-Trusted-Server | https://doi.org/10.48550/arXiv.2203.06735 |
| 396 | Personalized Subgraph Federated Learning | Jinheon Baek, Wonyong Jeong, Jiongdao Jin, Jaehong Yoon, Sung Ju Hwang | 2023-01-01 | arXiv | https://github.com/JinheonBaek/FED-PUB | https://doi.org/10.48550/arXiv.2206.10206 |
| 397 | Practical and General Backdoor Attacks Against Vertical Federated Learning | Yuexin Xuan, Xiaojun Chen, Zhendong Zhao, Bisheng Tang, Ye Dong | 2023-01-01 | Machine Learning and Knowledge Discovery in Databases: Research Track | https://github.com/xuanyx/BadVFL | http://dx.doi.org/10.1007/978-3-031-43415-0_24 |
| 398 | Federated Noisy Client Learning | Li Li, Huazhu Fu, Bo Han, Cheng-Zhong Xu, Ling Shao | 2023-01-01 | IEEE Transactions on Neural Networks and Learning Systems | https://github.com/TKH666/Fed-NCL | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10337775 |
| 399 | Reprogrammable-FL: Improving Utility-Privacy Tradeoff in Federated Learning via Model Reprogramming | Huzaifa Arif, Alex Gittens, Pin-Yu Chen | 2023-01-01 | 2023 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML) | https://github.com/IBM/reprogrammble-FL | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10136143 |
| 400 | RobustHealthFL: Robust Strategy Against Malicious Clients in Non-iid Healthcare Federated Learning* | Peng Xi, Wenjuan Tang, Kun Xie, Xuan Liu, Peng Zhao, Shaoliang Peng | 2023-01-01 | 2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) | https://github.com/xipengp/RobustHealthFL | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10385849 |
| 401 | SGFL: A Federated Learning Approach for Non-IID Data Using Semi-Supervised DCGAN | A. Rabiee, A. Ajdarloo, M. Rahmani | 2023-01-01 | 2023 13th International Conference on Computer and Knowledge Engineering (ICCKE) | https://github.com/apaliray03/SGFL | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10326270 |
| 402 | Spatial-Temporal Federated Learning for Lifelong Person Re-identification on Distributed Edges | Lei Zhang, Guanyu Gao, Huaizheng Zhang | 2023-01-01 | IEEE Transactions on Circuits and Systems for Video Technology | https://github.com/MSNLAB/Federated-Lifelong-Person-ReID | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10142016 |
| 403 | TradeFL: A Trading Mechanism for Cross-Silo Federated Learning | Shijing Yuan, Hongtao Lv, Hongze Liu, Chentao Wu, Song Guo, Zhi Liu, Hongyang Chen, Jie Li | 2023-01-01 | 2023 IEEE 43rd International Conference on Distributed Computing Systems (ICDCS) | https://github.com/user10963 | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10272449 |
| 404 | FederatedScope: A Flexible Federated Learning Platform for Heterogeneity | Yuexiang Xie, Zhen Wang, Dawei Gao, Daoyuan Chen, Liuyi Yao, Weirui Kuang, Yaliang Li, Bolin Ding, Jingren Zhou | 2023-01-01 | Proceedings of the VLDB Endowment (PVLDB), Volume 16, Issue 5 | https://github.com/alibaba/FederatedScope | https://dl.acm.org/doi/10.14778/3579075.3579081 |
| 405 | Reducing Training Time in Cross-Silo Federated Learning using Multigraph Topology | Tuong Do, Binh X. Nguyen, Vuong Pham, Toan Tran, Erman Tjiputra, Quang D. Tran, Anh Nguyen | 2023-01-01 | ICCV | https://github.com/aioz-ai/MultigraphFL | https://doi.org/10.1109/ICCV51070.2023.01778 |
| 406 | Federated Learning with Intermediate Representation Regularization | Ye Lin Tun, Chu Myaet Thwal, Yu Min Park, Seong-Bae Park, Choong Seon Hong | 2023-01-01 | 2023 IEEE International Conference on Big Data and Smart Computing (BigComp) | https://github.com/YLTun/FedIntR | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10066639 |
| 407 | FML-MIS: A Scheme of Privacy Protection and Model Generalization for Medical Images Segmentation via Federated Meta-learning | Mohan Yu, Heng Liu | 2023-01-01 | ICIG | https://github.com/yuwxl/FML-MIS | https://doi.org/10.1007/978-3-031-46314-3_11 |
| 408 | Federated Learning and Differential Privacy in AI-Based Surveillance Systems Model | J. Adiwijaya, V. R. Tanaya, Anderies, A. Chowanda | 2023-01-01 | 2023 14th International Conference on Information & Communication Technology and System (ICTS) | https://github.com/slimmyYer211/RMCS-PPCV_01 | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10330863 |
| 409 | Allosteric Feature Collaboration for Model-Heterogeneous Federated Learning | B. Yang, P. C. Yuen, Y. Zhang, A. Zeng | 2023-01-01 | IEEE Transactions on Neural Networks and Learning Systems | https://github.com/ybaoyao/AlFeCo | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10373104 |
| 410 | Brain Age Estimation Using Structural MRI: A Clustered Federated Learning Approach | Seyyed Saeid Cheshmi, Abtin Mahyar, Anita Soroush, Zahra Rezvani, Bahar J. Farahani | 2023-01-01 | 2023 IEEE International Conference on Omni-layer Intelligent Systems (COINS) | https://github.com/Abtinmy/Clustered-FL-BrainAGE | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10189329 |
| 411 | Byzantine-Robust Federated Learning with Optimal Statistical Rates and Privacy Guarantees | Banghua Zhu, Lun Wang, Qi Pang, Shuai Wang, Jiantao Jiao, Dawn Song, Michael I. Jordan | 2023-01-01 | arXiv | https://github.com/wanglun1996/secure-robust-federated-learning | https://doi.org/10.48550/arXiv.2205.11765 |
| 412 | Communication Efficient Federated Learning via Channel-wise Dynamic Pruning | Bo Tao, Cen Chen, Huimin Chen | 2023-01-01 | 2023 IEEE Wireless Communications and Networking Conference (WCNC) | https://github.com/tabo0/FedCDP | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10118879 |
| 413 | Disentangling Client Contributions: Improving Federated Learning Accuracy in the Presence of Heterogeneous Data | Chunming Liu, Daniyal M. Alghazzawi, Li Cheng, Gaoyang Liu, Chen Wang, Cheng Zeng, Yang Yang | 2023-01-01 | 2023 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom) | https://github.com/ChunmingLiu23/FedVa | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10491709 |
| 414 | F2MKD: Fog-enabled Federated Learning with Mutual Knowledge Distillation | Yusuke Yamasaki, Hideki Takase | 2023-01-01 | 2023 IEEE 20th Consumer Communications & Networking Conference (CCNC) | https://github.com/d3-ai/F2MKD | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10059910 |
| 415 | FLIS: Clustered Federated Learning Via Inference Similarity for Non-IID Data Distribution | Mahdi Morafah, Saeed Vahidian, Weijia Wang, Bill Lin | 2023-01-01 | IEEE Open Journal of the Computer Society | https://github.com/MMorafah/FLIS | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10081485 |
| 416 | Characterizing Internal Evasion Attacks in Federated Learning | Taejin Kim, Shubhranshu Singh, Nikhil Madaan, Carlee Joe-Wong | 2023-01-01 | AISTATS | https://github.com/tj-kim/pFedDef_v1 | https://proceedings.mlr.press/v206/kim23a.html |
| 417 | FedAudio: A Federated Learning Benchmark for Audio Tasks | Tuo Zhang, Tiantian Feng, Samiul Alam, Sunwoo Lee, Mi Zhang, Shrikanth S. Narayanan, Salman Avestimehr | 2023-01-01 | arXiv | https://github.com/zhang-tuo-pdf/FedAudio | https://doi.org/10.48550/arXiv.2210.15707 |
| 418 | FedForgery: Generalized Face Forgery Detection With Residual Federated Learning | Decheng Liu, Zhan Dang, Chunlei Peng, Yu Zheng, Shuang Li, Nannan Wang, Xinbo Gao | 2023-01-01 | IEEE Transactions on Information Forensics and Security | https://github.com/GANG370/FedForgery | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10177776 |
| 419 | FedGR: Federated Learning with Gravitation Regulation for Double Imbalance Distribution | Songyue Guo, Xu Yang, Jiyuan Feng, Ye Ding, Wei Wang, Yunqing Feng, Qing Liao | 2023-01-01 | DASFAA | https://github.com/Guosy-wxy/FedGR | https://doi.org/10.1007/978-3-031-30637-2_47 |
| 420 | FedGda: Model Aggregation Algorithm Based on Topological Density in Federated Graph Learning | Y. Li, X. Ren, X. Meng, T. Liu, H. Ling, C. Yu | 2023-01-01 | 2023 IEEE 5th Eurasia Conference on IOT, Communication and Engineering (ECICE) | https://github.com/xianglinllllll/renxiang | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10383071 |
| 421 | FedIIC: Towards Robust Federated Learning for Class-Imbalanced Medical Image Classification | Nannan Wu, Li Yu, Xin Yang, Kwang-Ting Cheng, Zengqiang Yan | 2023-01-01 | MICCAI | https://github.com/wnn2000/FedIIC | https://doi.org/10.1007/978-3-031-43895-0_65 |
| 422 | Federated Cross Learning for Medical Image Segmentation | Xuanang Xu, Hannah H. Deng, Tianyi Chen, Tianshu Kuang, Joshua C. Barber, Daeseung Kim, Jaime Gateno, James J. Xia, Pingkun Yan | 2023-01-01 | MIDL | https://github.com/DIAL-RPI/FedCross | https://proceedings.mlr.press/v227/xu24a.html |
| 423 | FedBR: Improving Federated Learning on Heterogeneous Data via Local Learning Bias Reduction | Yongxin Guo, Xiaoying Tang, Tao Lin | 2023-01-01 | ICML | https://github.com/lins-lab/fedbr | https://proceedings.mlr.press/v202/guo23g.html |
| 424 | Federated Learning With Spiking Neural Networks | Sadia Anjum Tumpa, Sonali Singh, Md Fahim Faysal Khan, Mahmut Taylan Kandemir, Vijaykrishnan Narayanan, Chita R. Das | 2023-01-01 | IEEE Transactions on Signal Processing | https://github.com/Intelligent-Computing-Lab-Yale/FedSNN | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9583900 |
| 425 | FedClassAvg: Local Representation Learning for Personalized Federated Learning on Heterogeneous Neural Networks | Jaehee Jang, Heonseok Ha, Dahuin Jung, Sungroh Yoon | 2023-01 | ICPP '22: Proceedings of the 51st International Conference on Parallel Processing | https://github.com/hukla/fedclassavg | https://dl.acm.org/doi/10.1145/3545008.3545073 |
| 426 | Self-Supervised Federated Adaptation for Multi-Site Brain Disease Diagnosis | Q. Yang, Q. Zhu, M. Wang, W. Shao, Z. Zhang, D. Zhang | 2023 | IEEE Transactions on Big Data | https://github.com/nuaayqm/S2FA | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10091149 |
| 427 | Online Knowledge Distillation via Mutual Contrastive Learning for Visual Recognition | C. Yang, Z. An, H. Zhou, F. Zhuang, Y. Xu, Q. Zhang | 2023 | IEEE Transactions on Pattern Analysis and Machine Intelligence | https://github.com/winycg/L-MCL | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10073628 |
| 428 | PerFedMask: Personalized Federated Learning with Optimized Masking Vectors | Mehdi Setayesh, Xiaoxiao Li, Vincent W. S. Wong | 2023 | ICLR | https://github.com/MehdiSet/PerFedMask | https://openreview.net/pdf?id=hxEIgUXLFF |
| 429 | Proportional Fairness in Federated Learning | Guojun Zhang, Saber Malekmohammadi, Xi Chen, Yaoliang Yu | 2023 | Trans. Mach. Learn. Res. | https://github.com/huawei-noah/Federated-Learning/tree/main/FairFL | https://openreview.net/forum?id=ryUHgEdWCQ |
| 430 | Where to Begin? On the Impact of Pre-Training and Initialization in Federated Learning | John Nguyen, Jianyu Wang, Kshitiz Malik, Maziar Sanjabi, Michael G. Rabbat | 2023 | arXiv | https://github.com/facebookresearch/where_to_begin | https://doi.org/10.48550/arXiv.2210.08090 |
| 431 | Test-Time Robust Personalization for Federated Learning | Liangze Jiang, Tao Lin | 2023 | arXiv | https://github.com/LINs-lab/FedTHE | https://doi.org/10.48550/arXiv.2205.10920 |
| 432 | Towards Understanding and Mitigating Dimensional Collapse in Heterogeneous Federated Learning | Yujun Shi, Jian Liang, Wenqing Zhang, Vincent Y. F. Tan, Song Bai | 2023 | arXiv | https://github.com/bytedance/FedDecorr | https://doi.org/10.48550/arXiv.2210.00226 |
| 433 | TransZero++: Cross Attribute-Guided Transformer for Zero-Shot Learning | S. Chen, Z. Hong, W. Hou, G. -S. Xie, Y. Song, J. Zhao, X. You, S. Yan, L. Shao | 2023 | IEEE Transactions on Pattern Analysis and Machine Intelligence | https://shiming-chen.github.io/TransZero-pp/TransZero-pp.html | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9987664 |
| 434 | Instance-wise Batch Label Restoration via Gradients in Federated Learning | Kailang Ma, Yu Sun, Jian Cui, Dawei Li, Zhenyu Guan, Jianwei Liu | 2023 | ICLR | https://github.com/BUAA-CST/iLRG | https://openreview.net/pdf?id=FIrQfNSOoTr |
| 435 | NVIDIA FLARE: Federated Learning from Simulation to Real-World | Holger R. Roth, Yan Cheng, Yuhong Wen, Isaac Yang, Ziyue Xu, Yuan-Ting Hsieh, Kristopher Kersten, Ahmed Harouni, Can Zhao, Kevin Lu, Zhihong Zhang, Wenqi Li, Andriy Myronenko, Dong Yang, Sean Yang, Nicola Rieke, Abood Quraini, Chester Chen, Daguang Xu, Nic Ma, Prerna Dogra, Mona Flores, Andrew Feng | 2023 | arXiv | https://github.com/NVIDIA/NVFlare | https://doi.org/10.48550/arXiv.2210.13291 |
| 436 | FedDAR: Federated Domain-Aware Representation Learning | Aoxiao Zhong, Hao He, Zhaolin Ren, Na Li, Quanzheng Li | 2023 | arXiv | https://github.com/zlz0414/FedDAR | https://doi.org/10.48550/arXiv.2209.04007 |
| 437 | IOP-FL: Inside-Outside Personalization for Federated Medical Image Segmentation | Meirui Jiang, Hongzheng Yang, Chen Cheng, Qi Dou | 2023 | IEEE Transactions on Medical Imaging | https://github.com/med-air/IOP-FL | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10086676 |
| 438 | Federated Multi-Organ Segmentation With Inconsistent Labels | Xuanang Xu, Hannah H. Deng, Jaime Gateno, Pingkun Yan | 2023 | IEEE Transactions on Medical Imaging | https://github.com/DIAL-RPI/Fed-MENU | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10107904 |
| 439 | Federated Brain Graph Evolution Prediction Using Decentralized Connectivity Datasets With Temporally-Varying Acquisitions | Z. Gürler, I. Rekik | 2023 | IEEE Transactions on Medical Imaging | https://github.com/basiralab/4D-FedGNN-Plus | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9964305 |
| 440 | FedDM: Federated Weakly Supervised Segmentation via Annotation Calibration and Gradient De-Conflicting | M. Zhu, Z. Chen, Y. Yuan | 2023 | IEEE Transactions on Medical Imaging | https://github.com/CityU-AIM-Group/FedDM | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10013742 |
| 441 | FLIP: A Provable Defense Framework for Backdoor Mitigation in Federated Learning | Kaiyuan Zhang, Guanhong Tao, Qiuling Xu, Siyuan Cheng, Shengwei An, Yingqi Liu, Shiwei Feng, Guangyu Shen, Pin-Yu Chen, Shiqing Ma, Xiangyu Zhang | 2023 | arXiv | https://github.com/KaiyuanZh/FLIP | https://doi.org/10.48550/arXiv.2210.12873 |
| 442 | Bayesian Collaborative Learning for Whole-Slide Image Classification | J. -G. Yu, Z. Wu, Y. Ming, S. Deng, Q. Wu, Z. Xiong, T. Yu, G. -S. Xia, Q. Jiang, Y. Li | 2023 | IEEE Transactions on Medical Imaging | https://github.com/Zero-We/BCL | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10034429 |
| 443 | A Systematic Evaluation of Federated Learning on Biomedical Natural Language Processing | Le Peng, Sicheng Zhou, Jiandong Chen, Rui Zhang, Ziyue Xu, Ju Sun | 2023 | arXiv | https://github.com/PL97/FedNLP | https://doi.org/10.48550/arXiv.2307.11254 |
| 444 | A New Framework of Swarm Learning Consolidating Knowledge From Multi-Center Non-IID Data for Medical Image Segmentation | Z. Gao, F. Wu, W. Gao, X. Zhuang | 2023 | IEEE Transactions on Medical Imaging | https://zmiclab.github.io/projects.html | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9943283 |
| 445 | A Dataset Auditing Method for Collaboratively Trained Machine Learning Models | Yangsibo Huang, Chun-Yin Huang, Xiaoxiao Li, Kai Li | 2023 | IEEE Transactions on Medical Imaging | https://github.com/Hazelsuko07/EMA | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9951407 |
| 446 | When Federated Learning Meets Pre-trained Language Models' Parameter-Efficient Tuning Methods | Zhuo Zhang, Yuanhang Yang, Yong Dai, Lizhen Qu, Zenglin Xu | 2022-12-20 | arXiv | https://github.com/iezhuozhuo/FedETuning/tree/deltaTuning | https://doi.org/10.48550/arXiv.2212.10025 |
| 447 | FedTADBench: Federated Time-series Anomaly Detection Benchmark | Fanxing Liu, Cheng Zeng, Le Zhang, Yingjie Zhou, Qing Mu, Yanru Zhang, Ling Zhang, Ce Zhu | 2022-12-19 | 2022 IEEE 24th Int Conf on High Performance Computing & Communications; 8th Int Conf on Data Science & Systems; 20th Int Conf on Smart City; 8th Int Conf on Dependability in Sensor, Cloud & Big Data Systems & Application (HPCC/DSS/SmartCity/DependSys) | https://github.com/fanxindiu2020/FedTADBench | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10074717 |
| 448 | FedSkip: Combatting Statistical Heterogeneity with Federated Skip Aggregation | Ziqing Fan, Yanfeng Wang, Jiangchao Yao, Lingjuan Lyu, Ya Zhang, Qi Tian | 2022-12-14 | 2022 IEEE International Conference on Data Mining (ICDM) | https://github.com/MediaBrain-SJTU/FedSkip | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10027627 |
| 449 | Robust Split Federated Learning for U-shaped Medical Image Networks | Ziyuan Yang, Yingyu Chen, Huijie Huangfu, Maosong Ran, Hui Wang, Xiaoxiao Li, Yi Zhang | 2022-12-13 | arXiv | https://github.com/Zi-YuanYang/RoS-FL | https://doi.org/10.48550/arXiv.2212.06378 |
| 450 | Collaborating Heterogeneous Natural Language Processing Tasks via Federated Learning | Chenhe Dong, Yuexiang Xie, Bolin Ding, Ying Shen, Yaliang Li | 2022-12-12 | arXiv | https://github.com/alibaba/FederatedScope/tree/master/federatedscope/nlp/hetero_tasks | https://doi.org/10.48550/arXiv.2212.05789 |
| 451 | FedRolex: Model-Heterogeneous Federated Learning with Rolling Sub-Model Extraction | Samiul Alam, Luyang Liu, Ming Yan, Mi Zhang | 2022-12-03 | NeurIPS | https://github.com/AIoT-MLSys-Lab/FedRolex | http://papers.nips.cc/paper_files/paper/2022/hash/bf5311df07f3efce97471921e6d2f159-Abstract-Conference.html |
| 452 | Federated Learning for Multi-Center Imaging Diagnostics: A Study in Cardiovascular Disease | Akis Linardos, Kaisar Kushibar, Sean Walsh, Polyxeni Gkontra, Karim Lekadir | 2022-12-01 | arXiv | https://github.com/Linardos/federated-HCM-diagnosis | https://arxiv.org/abs/2107.03901 |
| 453 | Personalized Retrogress-Resilient Federated Learning Toward Imbalanced Medical Data | Zhen Chen, Chen Yang, Meilu Zhu, Zhe Peng, Yixuan Yuan | 2022-12-01 | IEEE Transactions on Medical Imaging | https://github.com/CityU-AIM-Group/PRR-Imbalancehttps://github.com/CityU-AIM-Group/PRR-Imbalance | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9832948 |
| 454 | FedGS: Federated Graph-based Sampling with Arbitrary Client Availability | Zheng Wang, Xiaoliang Fan, Jianzhong Qi, Haibing Jin, Peizhen Yang, Siqi Shen, Cheng Wang | 2022-11-25 | arXiv | https://github.com/WwZzz/FedGS | http://arxiv.org/abs/2211.13975v3 |
| 455 | Federated Learning Hyper-Parameter Tuning from a System Perspective | Huanle Zhang, Lei Fu, Mi Zhang, Pengfei Hu, Xiuzhen Cheng, Prasant Mohapatra, Xin Liu | 2022-11-24 | arXiv | https://github.com/DataSysTech/FedTune | https://doi.org/10.48550/arXiv.2211.13656 |
| 456 | Robust Smart Home Face Recognition Under Starving Federated Data | Jaechul Roh, Yajun Fang | 2022-11-10 | 2022 6th International Conference on Universal Village (UV) | https://github.com/jcroh0508/FLATS | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10185525 |
| 457 | Enhancing Efficiency in Multidevice Federated Learning through Data Selection | Fan Mo, Mohammad Malekzadeh, Soumyajit Chatterjee, Fahim Kawsar, Akhil Mathur | 2022-11-08 | arXiv | https://github.com/dr-bell/data-centric-federated-learning | http://arxiv.org/abs/2211.04175v4 |
| 458 | FedFly: Toward Migration in Edge-Based Distributed Federated Learning | Rehmat Ullah, Di Wu, Paul Harvey, Peter Kilpatrick, Ivor T. A. Spence, Blesson Varghese | 2022-11-01 | IEEE Communications Magazine | https://github.com/qub-bless-on/FedFly | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9846940 |
| 459 | TorchFL: A Performant Library for Bootstrapping Federated Learning Experiments | Vivek Khimani, Shahin Jabbari | 2022-11-01 | arXiv | https://github.com/vivekkhimani/torchfl | https://doi.org/10.48550/arXiv.2211.00735 |
| 460 | Federated split GANs | Pranvera Kortoçi, Yilei Liang, Pengyuan Zhou, Lik-Hang Lee, Abbas Mehrabi, Pan Hui, Sasu Tarkoma, Jon Crowcroft | 2022-11 | FedEdge '22: Proceedings of the 1st ACM Workshop on Data Privacy and Federated Learning Technologies for Mobile Edge Network | https://github.com/YukariSonz/FSL-GAN | https://dl.acm.org/doi/10.1145/3556557.3557953 |
| 461 | SPATL: Salient Parameter Aggregation and Transfer Learning for Heterogeneous Federated Learning | Sixing Yu, Phuong Nguyen, Waqwoya Abebe, Wei Qian, Ali Anwar, Ali Jannesari | 2022-11 | SC22: International Conference for High Performance Computing, Networking, Storage and Analysis | https://github.com/yusx-swapp/SPATL | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10046104 |
| 462 | Machine Unlearning of Federated Clusters | Chao Pan, Jin Sima, Saurav Prakash, Vishal Rana, Olgica Milenkovic | 2022-10-28 | ICLR 2023 poster | https://github.com/thupchnsky/mufc | http://arxiv.org/abs/2210.16424v2 |
| 463 | Thinking Two Moves Ahead: Anticipating Other Users Improves Backdoor Attacks in Federated Learning | Yuxin Wen, Jonas Geiping, Liam H Fowl, Hossein Souri, Rama Chellappa, Micah Goldblum, Tom Goldstein | 2022-10-17 | arXiv | https://github.com/YuxinWenRick/thinking-two-moves-ahead | https://doi.org/10.48550/arXiv.2210.09305 |
| 464 | Towards Federated Learning against Noisy Labels via Local Self-Regularization | Xuefeng Jiang, Sheng Sun, Yuwei Wang, Min Liu | 2022-10-17 | CIKM | https://github.com/Sprinter1999/FedLSR | https://doi.org/10.1145/3511808.3557475 |
| 465 | Federated Stain Normalization for Computational Pathology | Nicolas Wagner, Moritz Fuchs, Yuri Tolkach, Anirban Mukhopadhyay | 2022-09-29 | arXiv | https://github.com/MECLabTUDA/BottleGAN | http://arxiv.org/abs/2209.14849v1 |
| 466 | Investigating the Predictive Reproducibility of Federated Graph Neural Networks using Medical Datasets | Mehmet Yigit Balik, Arwa Rekik, Islem Rekik | 2022-09-13 | arXiv | https://github.com/basiralab/reproducibleFedGNN | http://arxiv.org/abs/2209.06032v1 |
| 467 | Communication-Efficient and Privacy-Preserving Feature-based Federated Transfer Learning | Feng Wang, Mustafa Cenk Gursoy, Senem Velipasalar | 2022-09-12 | GLOBECOM 2022 - 2022 IEEE Global Communications Conference | https://github.com/wfwf10/Feature-based-Federated-Transfer-Learning | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10000612 |
| 468 | SplitAVG: A Heterogeneity-Aware Federated Deep Learning Method for Medical Imaging | Miao Zhang, Liangqiong Qu, Praveer Singh, Jayashree Kalpathy-Cramer, Daniel L. Rubin | 2022-09-01 | IEEE Journal of Biomedical and Health Informatics | https://github.com/zm17943/SplitAVG | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9806163 |
| 469 | Federated Learning of Large Models at the Edge via Principal Sub-Model Training | Yue Niu, Saurav Prakash, Souvik Kundu, Sunwoo Lee, Salman Avestimehr | 2022-08-28 | arXiv | https://github.com/yuehniu/modeldecomp-fl | https://doi.org/10.48550/arXiv.2208.13141 |
| 470 | Lottery Aware Sparsity Hunting: Enabling Federated Learning on Resource-Limited Edge | Sara Babakniya, Souvik Kundu, Saurav Prakash, Yue Niu, Salman Avestimehr | 2022-08-27 | Submitted to ICLR 2023 | https://github.com/SaraBabakN/flash_fl | http://arxiv.org/abs/2208.13092v3 |
| 471 | FedComm: Understanding Communication Protocols for Edge-based Federated Learning | Gary Cleland, Di Wu, Rehmat Ullah, Blesson Varghese | 2022-08-18 | 2022 IEEE/ACM 15th International Conference on Utility and Cloud Computing (UCC) | https://github.com/qub-blesson/edComm | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10061797 |
| 472 | Long-Short History of Gradients Is All You Need: Detecting Malicious and Unreliable Clients in Federated Learning | Ashish Gupta, Tie Luo, Mao V. Ngo, Sajal K. Das | 2022-08-14 | ESORICS | https://github.com/LabSAINT/MUD-HoG_Federated_Learning | https://doi.org/10.1007/978-3-031-17143-7_22 |
| 473 | FederatedScope-GNN: Towards a Unified, Comprehensive and Efficient Package for Federated Graph Learning | Zhen Wang, Weirui Kuang, Yuexiang Xie, Liuyi Yao, Yaliang Li, Bolin Ding, Jingren Zhou | 2022-08-14 | KDD | https://github.com/alibaba/FederatedScope | https://doi.org/10.1145/3534678.3539112 |
| 474 | FLDetector: Defending Federated Learning Against Model Poisoning Attacks via Detecting Malicious Clients | Zaixi Zhang, Xiaoyu Cao, Jinyuan Jia, Neil Zhenqiang Gong | 2022-08-14 | KDD | https://github.com/zaixizhang/FLDetector | https://doi.org/10.1145/3534678.3539231 |
| 475 | Connecting Low-Loss Subspace for Personalized Federated Learning | Seok-Ju Hahn, Minwoo Jeong, Junghye Lee | 2022-08-14 | KDD '22: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining | http://github.com/vaseline555/SuPerFed | https://dl.acm.org/doi/10.1145/3534678.3539254 |
| 476 | UniFed: All-In-One Federated Learning Platform to Unify Open-Source Frameworks | Xiaoyuan Liu, Tianneng Shi, Chulin Xie, Qinbin Li, Kangping Hu, Haoyu Kim, Xiaojun Xu, The-Anh Vu-Le, Zhen Huang, Arash Nourian, Bo Li, Dawn Song | 2022-07-21 | arXiv | https://github.com/AI-secure/FLBenchmark-toolkit | http://arxiv.org/abs/2207.10308v3 |
| 477 | FLAIR: Federated Learning Annotated Image Repository | Congzheng Song, Filip Granqvist, Kunal Talwar | 2022-07-18 | NeurIPS | https://github.com/apple/ml-flair | http://papers.nips.cc/paper_files/paper/2022/hash/f64e55d03e2fe61aa4114e49cb654acb-Abstract-Datasets_and_Benchmarks.html |
| 478 | Suppressing Poisoning Attacks on Federated Learning for Medical Imaging | Naif Alkhunaizi, Dmitry Kamzolov, Martin Takác, Karthik Nandakumar | 2022-07-15 | MICCAI | https://github.com/Naiftt/SPAFD | https://doi.org/10.1007/978-3-031-16452-1_64 |
| 479 | Personalizing Federated Medical Image Segmentation via Local Calibration | Jiacheng Wang, Yueming Jin, Liansheng Wang | 2022-07-11 | arXiv | https://github.com/jcwang123/FedLC | http://arxiv.org/abs/2207.04655v1 |
| 480 | Federated Dynamic Sparse Training: Computing Less, Communicating Less, Yet Learning Better | Sameer Bibikar, Haris Vikalo, Zhangyang Wang, Xiaohan Chen | 2022-06-30 | arXiv | https://github.com/bibikar/feddst | https://arxiv.org/abs/2112.09824 |
| 481 | HarmoFL: Harmonizing Local and Global Drifts in Federated Learning on Heterogeneous Medical Images | Meirui Jiang, Zirui Wang, Qi Dou | 2022-06-30 | arXiv | https://github.com/med-air/HarmoFL | https://arxiv.org/abs/2112.10775 |
| 482 | Dynamic Bank Learning for Semi-supervised Federated Image Diagnosis with Class Imbalance | Meirui Jiang, Hongzheng Yang, Xiaoxiao Li, Quande Liu, Pheng-Ann Heng, Qi Dou | 2022-06-27 | MICCAI | https://github.com/med-air/imFedSemi | https://doi.org/10.1007/978-3-031-16437-8_19 |
| 483 | Robust One Round Federated Learning with Predictive Space Bayesian Inference | Mohsin Hasan, Zehao Zhang, Kaiyang Guo, Mahdi Karami, Guojun Zhang, Xi Chen, Pascal Poupart | 2022-06-20 | arXiv | https://github.com/hasanmohsin/FedPredSpace_1Round | https://doi.org/10.48550/arXiv.2206.09526 |
| 484 | Motley: Benchmarking Heterogeneity and Personalization in Federated Learning | Shanshan Wu, Tian Li, Zachary Charles, Yu Xiao, Ken Ziyu Liu, Zheng Xu, Virginia Smith | 2022-06-18 | arXiv | https://github.com/google-research/federated/tree/master/personalization_benchmark | https://doi.org/10.48550/arXiv.2206.09262 |
| 485 | Federated Optimization Algorithms with Random Reshuffling and Gradient Compression | Abdurakhmon Sadiev, Grigory Malinovsky, Eduard Gorbunov, Igor Sokolov, Ahmed Khaled, Konstantin Burlachenko, Peter Richtárik | 2022-06-14 | arXiv | https://github.com/IgorSokoloff/rr_with_compression_experiments_source_code | http://arxiv.org/abs/2206.07021v2 |
| 486 | FedHPO-B: A Benchmark Suite for Federated Hyperparameter Optimization | Zhen Wang, Weirui Kuang, Ce Zhang, Bolin Ding, Yaliang Li | 2022-06-08 | Submitted to ICLR 2023 | https://github.com/alibaba/FederatedScope/tree/master/benchmark/FedHPOB | http://arxiv.org/abs/2206.03966v4 |
| 487 | Hypernetwork-based Personalized Federated Learning for Multi-Institutional CT Imaging | Ziyuan Yang, Wenjun Xia, Zexin Lu, Yingyu Chen, Xiaoxiao Li, Yi Zhang | 2022-06-08 | arXiv | https://github.com/Zi-YuanYang/HyperFed | https://doi.org/10.48550/arXiv.2206.03709 |
| 488 | pFL-Bench: A Comprehensive Benchmark for Personalized Federated Learning | Daoyuan Chen, Dawei Gao, Weirui Kuang, Yaliang Li, Bolin Ding | 2022-06-08 | NeurIPS | https://github.com/alibaba/FederatedScope/tree/master/benchmark/pFL-Bench | http://papers.nips.cc/paper_files/paper/2022/hash/3cc03e19fed71a2b9347d83921ca2e7d-Abstract-Datasets_and_Benchmarks.html |
| 489 | A Benchmark for Federated Hetero-Task Learning | Liuyi Yao, Dawei Gao, Zhen Wang, Yuexiang Xie, Weirui Kuang, Daoyuan Chen, Haohui Wang, Chenhe Dong, Bolin Ding, Yaliang Li | 2022-06-07 | arXiv | https://github.com/alibaba/FederatedScope/tree/master/benchmark/B-FHTL | https://doi.org/10.48550/arXiv.2206.03436 |
| 490 | FedHarmony: Unlearning Scanner Bias with Distributed Data | Nicola K Dinsdale, Mark Jenkinson, Ana IL Namburete | 2022-05-31 | arXiv | https://github.com/nkdinsdale/FedHarmony | http://arxiv.org/abs/2205.15970v1 |
| 491 | Federated Neural Bandits | Zhongxiang Dai, Yao Shu, Arun Verma, Flint Xiaofeng Fan, Bryan Kian Hsiang Low, Patrick Jaillet | 2022-05-28 | ICLR 2023 poster | https://github.com/daizhongxiang/Federated-Neural-Bandits | http://arxiv.org/abs/2205.14309v2 |
| 492 | FedILC: Weighted Geometric Mean and Invariant Gradient Covariance for Federated Learning on Non-IID Data | Mike He Zhu, Léna Néhale Ezzine, Dianbo Liu, Yoshua Bengio | 2022-05-19 | arXiv | https://github.com/mikemikezhu/FedILC | https://doi.org/10.48550/arXiv.2205.09305 |
| 493 | Recovering Private Text in Federated Learning of Language Models | Samyak Gupta, Yangsibo Huang, Zexuan Zhong, Tianyu Gao, Kai Li, Danqi Chen | 2022-05-17 | NeurIPS | https://github.com/Princeton-SysML/FILM | http://papers.nips.cc/paper_files/paper/2022/hash/35b5c175e139bff5f22a5361270fce87-Abstract-Conference.html |
| 494 | ResSFL: A Resistance Transfer Framework for Defending Model Inversion Attack in Split Federated Learning | Jingtao Li, Adnan Siraj Rakin, Xing Chen, Zhezhi He, Deliang Fan, Chaitali Chakrabarti | 2022-05-09 | 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | https://github.com/zlijingtao/ResSFL | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9880307 |
| 495 | FedCVT: Semi-supervised Vertical Federated Learning with Cross-view Training | Yan Kang, Yang Liu, Xinle Liang | 2022-05-04 | ACM Transactions on Intelligent Systems and Technology (TIST), Volume 13, Issue 4 | https://github.com/yankang18/FedCVT | https://dl.acm.org/doi/10.1145/3510031 |
| 496 | FedNest: Federated Bilevel, Minimax, and Compositional Optimization | Davoud Ataee Tarzanagh, Mingchen Li, Christos Thrampoulidis, Samet Oymak | 2022-05-04 | Proceedings of the 39th International Conference on Machine Learning, PMLR 162:21146-21179, 2022 | https://github.com/ucr-optml/FedNest | http://arxiv.org/abs/2205.02215v3 |
| 497 | GRNN: Generative Regression Neural Network—A Data Leakage Attack for Federated Learning | Hanchi Ren, Jingjing Deng, Xianghua Xie | 2022-05-04 | ACM Transactions on Intelligent Systems and Technology (TIST), Volume 13, Issue 4 | https://github.com/Rand2AI/GRNN | https://dl.acm.org/doi/10.1145/3510032 |
| 498 | Improving response time of home IoT services in federated learning | Dongjun Hwang, Hyunsu Mun, Youngseok Lee | 2022-05 | SAC '22: Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing | https://github.com/HwangDongJun/Federated_Learning_using_Websockets | https://dl.acm.org/doi/10.1145/3477314.3508380 |
| 499 | FEDIC: Federated Learning on Non-IID and Long-Tailed Data via Calibrated Distillation | Xinyi Shang, Yang Lu, Yiu-Ming Cheung, Hanzi Wang | 2022-04-30 | 2022 IEEE International Conference on Multimedia and Expo (ICME) | https://github.com/shangxinyi/FEDIC | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9860009 |
| 500 | Federated Learning on Heterogeneous and Long-Tailed Data via Classifier Re-Training with Federated Features | Xinyi Shang, Yang Lu, Gang Huang, Hanzi Wang | 2022-04-28 | IJCAI | https://github.com/shangxinyi/CReFF-FL | https://doi.org/10.24963/ijcai.2022/308 |
| 501 | CXR-FL: Deep Learning-Based Chest X-ray Image Analysis Using Federated Learning | Filip Slazyk, Przemyslaw Jablecki, Aneta Lisowska, Maciej Malawski, Szymon Plotka | 2022-04-11 | ICCS | https://github.com/SanoScience/CXR-FL | https://doi.org/10.1007/978-3-031-08754-7_50 |
| 502 | FedCorr: Multi-Stage Federated Learning for Label Noise Correction | Jingyi Xu, Zihan Chen, Tony Q. S. Quek, Kai Fong Ernest Chong | 2022-04-10 | 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | https://github.com/Xu-Jingyi/FedCorr | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9878965 |
| 503 | Federated Learning from Only Unlabeled Data with Class-conditional-sharing Clients | Nan Lu, Zhao Wang, Xiaoxiao Li, Gang Niu, Qi Dou, Masashi Sugiyama | 2022-04-07 | ICLR | https://github.com/lunanbit/FedUL | https://openreview.net/forum?id=WHA8009laxu |
| 504 | User-Level Differential Privacy against Attribute Inference Attack of Speech Emotion Recognition in Federated Learning | Tiantian Feng, Raghuveer Peri, Shrikanth Narayanan | 2022-04-05 | arXiv | https://github.com/usc-sail/fed-ser-leakage | https://doi.org/10.48550/arXiv.2204.02500 |
| 505 | RSCFed: Random Sampling Consensus Federated Semi-supervised Learning | Xiaoxiao Liang, Yiqun Lin, Huazhu Fu, Lei Zhu, Xiaomeng Li | 2022-03-26 | 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | https://github.com/XMed-Lab/RSCFed | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9878902 |
| 506 | Efficient Split-Mix Federated Learning for On-Demand and In-Situ Customization | Junyuan Hong, Haotao Wang, Zhangyang Wang, Jiayu Zhou | 2022-03-18 | ICLR | https://github.com/illidanlab/SplitMix | https://openreview.net/forum?id=_QLmakITKg |
| 507 | Acceleration of Federated Learning with Alleviated Forgetting in Local Training | Chencheng Xu, Zhiwei Hong, Minlie Huang, Tao Jiang | 2022-03-05 | ICLR | https://github.com/Zoesgithub/FedReg | https://openreview.net/forum?id=541PxiEKN3F |
| 508 | Vertical Federated Principal Component Analysis and Its Kernel Extension on Feature-wise Distributed Data | Yiu-ming Cheung, Juyong Jiang, Feng Yu, Jian Lou | 2022-03-03 | arXiv | https://github.com/juyongjiang/VFedPCA-VFedAKPCA | http://arxiv.org/abs/2203.01752v1 |
| 509 | FedDrive: Generalizing Federated Learning to Semantic Segmentation in Autonomous Driving | Lidia Fantauzzo, Eros Fanì, Debora Caldarola, Antonio Tavera, Fabio Cermelli, Marco Ciccone, Barbara Caputo | 2022-02-28 | 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) | https://feddrive.github.io | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9981098 |
| 510 | Sky Computing: Accelerating Geo-distributed Computing in Federated Learning | Jie Zhu, Shenggui Li, Yang You | 2022-02-24 | arXiv | https://github.com/hpcaitech/SkyComputing | https://arxiv.org/abs/2202.11836 |
| 511 | Privacy Leakage of Adversarial Training Models in Federated Learning Systems | Jingyang Zhang, Yiran Chen, Hai Helen Li | 2022-02-21 | CVPR Workshops | https://github.com/zjysteven/PrivayAttack_AT_FL | https://doi.org/10.1109/CVPRW56347.2022.00021 |
| 512 | Factorized-FL: Agnostic Personalized Federated Learning with Kernel Factorization & Similarity Matching | Wonyong Jeong, Sung Ju Hwang | 2022-02-01 | arXiv | https://github.com/wyjeong/Factorized-FL | https://arxiv.org/abs/2202.00270 |
| 513 | FedGCN: Convergence-Communication Tradeoffs in Federated Training of Graph Convolutional Networks | Yuhang Yao, Weizhao Jin, Srivatsan Ravi, Carlee Joe-Wong | 2022-01-28 | NeurIPS 2023 | https://github.com/yh-yao/FedGCN | http://arxiv.org/abs/2201.12433v7 |
| 514 | FedMed-GAN: Federated Domain Translation on Unsupervised Cross-Modality Brain Image Synthesis | Jinbao Wang, Guoyang Xie, Yawen Huang, Jiayi Lyu, Yefeng Zheng, Feng Zheng, Yaochu Jin | 2022-01-22 | OpenReview | https://github.com/M-3LAB/FedMed-GAN | http://arxiv.org/abs/2201.08953v3 |
| 515 | Towards Federated Bayesian Network Structure Learning with Continuous Optimization | Ignavier Ng, Kun Zhang | 2022-01-01 | arXiv | https://github.com/ignavierng/notears-admm | https://arxiv.org/abs/2110.09356 |
| 516 | DSFL: Dynamic Sparsification for Federated Learning | Mahdi Beitollahi, Mingrui Liu, Ning Lu | 2022-01-01 | 2022 5th International Conference on Communications, Signal Processing, and their Applications (ICCSPA) | https://github.com/mahdibeit/DSFL | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10019204 |
| 517 | ProgFed: Effective, Communication, and Computation Efficient Federated Learning by Progressive Training | Hui-Po Wang, Sebastian U. Stich, Yang He, Mario Fritz | 2022-01-01 | arXiv | https://github.com/a514514772/ProgFed | https://arxiv.org/abs/2110.05323 |
| 518 | Privacy-preserving Model Training for Disease Prediction Using Federated Learning with Differential Privacy | Amol Khanna, Vincent Schaffer, Gamze Gürsoy, Mark Gerstein | 2022-01-01 | 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) | https://github.com/gersteinlab/idash20FL | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9871742 |
| 519 | Local Learning Matters: Rethinking Data Heterogeneity in Federated Learning | Matías Mendieta, Taojiannan Yang, Pu Wang, Minwoo Lee, Zhengming Ding, Chen Chen | 2022-01-01 | 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | https://github.com/mmendiet/FedAlign | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9880310 |
| 520 | GraphFL: A Federated Learning Framework for Semi-Supervised Node Classification on Graphs | Binghui Wang, Ang Li, Meng Pang, Hai Li, Yiran Chen | 2022-01-01 | 2022 IEEE International Conference on Data Mining (ICDM) | https://github.com/binghuiivang/GraphFL | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10027604 |
| 521 | Fidel: Reconstructing Private Training Samples from Weight Updates in Federated Learning | David Enthoven, Zaid Al-Ars | 2022-01-01 | 2022 9th International Conference on Internet of Things: Systems, Management and Security (IOTSMS) | https://github.com/Davidenthoven/Fidel-Reconstruction-Demo | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10062088 |
| 522 | Federated Time-Dependent GNN Learning from Brain Connectivity Data with Missing Timepoints | Zeynep Gürler, Islem Rekik | 2022-01-01 | PRIME@MICCAI | https://github.com/basiralab/4D-FED-GNN | https://doi.org/10.1007/978-3-031-16919-9_1 |
| 523 | Federated Learning with Positive and Unlabeled Data | Xinyang Lin, Hanting Chen, Yixing Xu, Chao Xu, Xiaolin Gui, Yiping Deng, Yunhe Wang | 2022-01-01 | arXiv | https://github.com/littleSunlxy/FedPU-torch | https://arxiv.org/abs/2106.10904 |
| 524 | Federated Learning Algorithms with Heterogeneous Data Distributions: An Empirical Evaluation | Alessio Mora, Davide Fantini, Paolo Bellavista | 2022-01-01 | 2022 IEEE/ACM 7th Symposium on Edge Computing (SEC) | https://github.com/alessiomora/fI_algorithms_non_iid | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9996788 |
| 525 | Rethinking Architecture Design for Tackling Data Heterogeneity in Federated Learning | Liangqiong Qu, Yuyin Zhou, Paul Pu Liang, Yingda Xia, Feifei Wang, Ehsan Adeli, Li Fei-Fei, Daniel L. Rubin | 2022-01-01 | 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | https://github.com/Liangqiong/ViT-FL-main | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9880336 |
| 526 | Contractible Regularization for Federated Learning on Non-IID Data | Zifan Chen, Zhe Wu, Xian Wu, Li Zhang, Jie Zhao, Yangtian Yan, Yefeng Zheng | 2022-01-01 | 2022 IEEE International Conference on Data Mining (ICDM) | https://github.com/czifan/ConTre.pytorch | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10027753 |
| 527 | A Trustless Federated Framework for Decentralized and Confidential Deep Learning | C. Li, Q. Shen, C. Xiang, B. Ramesh | 2022-01-01 | 2022 IEEE 1st Global Emerging Technology Blockchain Forum: Blockchain & Beyond (iGETblockchain) | https://github.com/s-elo/DNN-Blockchain | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10087146 |
| 528 | Deep Federated Learning for Autonomous Driving | Anh Nguyen, Tuong Do, Minh Tran, Binh X. Nguyen, Chien Duong, Tu Phan, Erman Tjiputra, Quang D. Tran | 2022-01-01 | 2022 IEEE Intelligent Vehicles Symposium (IV) | https://github.com/aioz-ai/FADNet | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9827020 |
| 529 | A Coupled Design of Exploiting Record Similarity for Practical Vertical Federated Learning | Zhaomin Wu, Qinbin Li, Bingsheng He | 2022-01-01 | arXiv | https://github.com/Xtra-Computing/FedSim | https://arxiv.org/abs/2106.06312 |
| 530 | A Novel Optimized Asynchronous Federated Learning Framework | Zhicheng Zhou, Hailong Chen, Kunhua Li, Fei Hu, Bingjie Yan, Jieren Cheng, Xuyan Wei, Bernie Liu, Xiulai Li, Fuwen Chen, Yongji Sui | 2022-01-01 | 2021 IEEE 23rd Int Conf on High Performance Computing & Communications; 7th Int Conf on Data Science & Systems; 19th Int Conf on Smart City; 7th Int Conf on Dependability in Sensor, Cloud & Big Data Systems & Application (HPCC/DSS/SmartCity/DependSys) | https://github.com/RobAI-Lab/NAFL | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9781177 |
| 531 | Continual Learning of Dynamical Systems With Competitive Federated Reservoir Computing | Leonard Bereska, Efstratios Gavves | 2022-01-01 | CoLLAs | https://github.com/leonardbereska/multiheadreservoir | https://proceedings.mlr.press/v199/bereska22a.html |
| 532 | Adapt to Adaptation: Learning Personalization for Cross-Silo Federated Learning | Jun Luo, Shandong Wu | 2022-01-01 | arXiv | https://github.com/ljaiverson/pFL-APPLE | https://arxiv.org/abs/2110.08394 |
| 533 | Adaptive Weight Aggregation in Federated Learning for Brain Tumor Segmentation | Muhammad Irfan Khan, Mojtaba Jafaritadi, Esa Alhoniemi, Elina Kontio, Suleiman A. Khan | 2022-01-01 | BrainLes@MICCAI | https://github.com/dskhanirfan/FeTS2021 | https://doi.org/10.1007/978-3-031-09002-8_40 |
| 534 | An Agnostic Approach to Federated Learning with Class Imbalance | Zebang Shen, Juan Cerviño, Hamed Hassani, Alejandro Ribeiro | 2022-01-01 | ICLR | https://github.com/shenzebang/Federated-Learning-Pytorch | https://openreview.net/forum?id=Xo0lbDt975 |
| 535 | Byzantine-robust Federated Learning through Collaborative Malicious Gradient Filtering | Jian Xu, Shao-Lun Huang, Linqi Song, Tian Lan | 2022-01-01 | 2022 IEEE 42nd International Conference on Distributed Computing Systems (ICDCS) | https://github.com/JianXu95/SignGuard | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9912299 |
| 536 | Optimal Client Sampling for Federated Learning | Wenlin Chen, Samuel Horváth, Peter Richtárik | 2022 | arXiv | https://github.com/SamuelHorvath/FL-optimal-client-sampling | https://arxiv.org/abs/2010.13723 |
| 537 | Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems | S. Huai, D. Liu, H. Kong, X. Luo, W. Liu, R. Subramaniam, C. Makaya, Q. Lin | 2022 | 2022 IEEE 40th International Conference on Computer Design (ICCD) | https://github.com/ntuliuteam/Collate | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9978336 |
| 538 | FedFR: Joint Optimization Federated Framework for Generic and Personalized Face Recognition | Chih-Ting Liu, Chien-Yi Wang, Shao-Yi Chien, Shang-Hong Lai | 2021-12-23 | arXiv | https://github.com/jackie840129/FedFR | http://arxiv.org/abs/2112.12496v3 |
| 539 | Evaluating Gradient Inversion Attacks and Defenses in Federated Learning | Yangsibo Huang, Samyak Gupta, Zhao Song, Kai Li, Sanjeev Arora | 2021-11-30 | NeurIPS | https://github.com/Princeton-SysML/GradAttack | https://proceedings.neurips.cc/paper/2021/hash/3b3fff6463464959dcd1b68d0320f781-Abstract.html |
| 540 | Anomaly Localization in Model Gradients Under Backdoor Attacks Against Federated Learning | Zeki Bilgin | 2021-11-29 | arXiv | https://github.com/ArcelikAcikKaynak/Federated_Learning | https://arxiv.org/abs/2111.14683 |
| 541 | FedCV: A Federated Learning Framework for Diverse Computer Vision Tasks | Chaoyang He, Alay Dilipbhai Shah, Zhenheng Tang, Di Fan, Adarshan Naiynar Sivashunmugam, Keerti Bhogaraju, Mita Shimpi, Li Shen, Xiaowen Chu, Mahdi Soltanolkotabi, Salman Avestimehr | 2021-11-22 | arXiv | https://github.com/FedML-AI/FedCV | https://arxiv.org/abs/2111.11066 |
| 542 | Reconfigurable Intelligent Surface Enabled Federated Learning: A Unified Communication-Learning Design Approach | Hang Liu, Xiaojun Yuan, Ying-Jun Angela Zhang | 2021-11-01 | IEEE Transactions on Wireless Communications | https://github.com/liuhang1994/RIS-FL | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9451567 |
| 543 | Revealing and Protecting Labels in Distributed Training | Trung Dang, Om Thakkar, Swaroop Ramaswamy, Rajiv Mathews, Peter Chin, Françoise Beaufays | 2021-10-31 | NeurIPS 2021 Poster | https://github.com/googleinterns/learning-bag-of-words | http://arxiv.org/abs/2111.00556v1 |
| 544 | Differentially Private Federated Bayesian Optimization with Distributed Exploration | Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet | 2021-10-27 | NeurIPS 2021 Poster | https://github.com/daizhongxiang/Differentially-Private-Federated-Bayesian-Optimization | http://arxiv.org/abs/2110.14153v1 |
| 545 | FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective | Jingwei Sun, Ang Li, Louis DiValentin, Amin Hassanzadeh, Yiran Chen, Hai Li | 2021-10-26 | NeurIPS | https://github.com/jeremy313/FL-WBC | https://proceedings.neurips.cc/paper/2021/hash/692baebec3bb4b53d7ebc3b9fabac31b-Abstract.html |
| 546 | Fault-Tolerant Federated Reinforcement Learning with Theoretical Guarantee | Flint Xiaofeng Fan, Yining Ma, Zhongxiang Dai, Wei Jing, Cheston Tan, Bryan Kian Hsiang Low | 2021-10-26 | NeurIPS | https://github.com/flint-xf-fan/Byzantine-Federeated-RL | https://proceedings.neurips.cc/paper/2021/hash/080acdcce72c06873a773c4311c2e464-Abstract.html |
| 547 | CAFE: Catastrophic Data Leakage in Vertical Federated Learning | Xiao Jin, Pin-Yu Chen, Chia-Yi Hsu, Chia-Mu Yu, Tianyi Chen | 2021-10-26 | arXiv | https://github.com/DeRafael/CAFE | https://arxiv.org/abs/2110.15122 |
| 548 | The Skellam Mechanism for Differentially Private Federated Learning | Naman Agarwal, Peter Kairouz, Ziyu Liu | 2021-10-11 | NeurIPS | https://github.com/google-research/federated/tree/master/distributed_dp | https://proceedings.neurips.cc/paper/2021/hash/285baacbdf8fda1de94b19282acd23e2-Abstract.html |
| 549 | Personalized Retrogress-Resilient Framework for Real-World Medical Federated Learning | Zhen Chen, Meilu Zhu, Chen Yang, Yixuan Yuan | 2021-10-01 | MICCAI | https://github.com/CityU-AIM-Group/PRR-FL | https://doi.org/10.1007/978-3-030-87199-4_33 |
| 550 | Federated Multi-Task Learning under a Mixture of Distributions | Othmane Marfoq, Giovanni Neglia, Aurélien Bellet, Laetitia Kameni, Richard Vidal | 2021-08-23 | NeurIPS | https://github.com/omarfoq/FedEM | https://proceedings.neurips.cc/paper/2021/hash/82599a4ec94aca066873c99b4c741ed8-Abstract.html |
| 551 | Addressing Algorithmic Disparity and Performance Inconsistency in Federated Learning | Sen Cui, Weishen Pan, Jian Liang, Changshui Zhang, Fei Wang | 2021-08-19 | NeurIPS | https://github.com/cuis15/FCFL | https://proceedings.neurips.cc/paper/2021/hash/db8e1af0cb3aca1ae2d0018624204529-Abstract.html |
| 552 | Personalized Federated Learning With Gaussian Processes | Idan Achituve, Aviv Shamsian, Aviv Navon, Gal Chechik, Ethan Fetaya | 2021-06-29 | NeurIPS | https://idanachituve.github.io/projects/pFedGP/ | https://proceedings.neurips.cc/paper/2021/hash/46d0671dd4117ea366031f87f3aa0093-Abstract.html |
| 553 | Federated Graph Classification over Non-IID Graphs | Han Xie, Jing Ma, Li Xiong, Carl Yang | 2021-06-25 | NeurIPS 2021 Poster | https://github.com/Oxfordblue7/GCFL | http://arxiv.org/abs/2106.13423v5 |
| 554 | Subgraph Federated Learning with Missing Neighbor Generation | Ke Zhang, Carl Yang, Xiaoxiao Li, Lichao Sun, Siu-Ming Yiu | 2021-06-25 | NeurIPS | https://github.com/zkhku/fedsage | https://proceedings.neurips.cc/paper/2021/hash/34adeb8e3242824038aa65460a47c29e-Abstract.html |
| 555 | Optimality and Stability in Federated Learning: A Game-theoretic Approach | Kate Donahue, Jon M. Kleinberg | 2021-06-17 | NeurIPS | https://github.com/kpdonahue/model_sharing_games | https://proceedings.neurips.cc/paper/2021/hash/09a5e2a11bea20817477e0b1dfe2cc21-Abstract.html |
| 556 | Federated Semi-supervised Medical Image Classification via Inter-client Relation Matching | Quande Liu, Hongzheng Yang, Qi Dou, Pheng-Ann Heng | 2021-06-16 | arXiv | https://github.com/liuquande/FedIRM | http://arxiv.org/abs/2106.08600v1 |
| 557 | On Large-Cohort Training for Federated Learning | Zachary Charles, Zachary Garrett, Zhouyuan Huo, Sergei Shmulyian, Virginia Smith | 2021-06-15 | NeurIPS | https://github.com/google-research/federated/tree/f4e26c1b9b47ac320e520a8b9943ea2c5324b8c2/large_cohort | https://proceedings.neurips.cc/paper/2021/hash/ab9ebd57177b5106ad7879f0896685d4-Abstract.html |
| 558 | CRFL: Certifiably Robust Federated Learning against Backdoor Attacks | Chulin Xie, Minghao Chen, Pin-Yu Chen, Bo Li | 2021-06-15 | ICML | https://github.com/AI-secure/CRFL | http://proceedings.mlr.press/v139/xie21a.html |
| 559 | Federated Learning for Internet of Things: A Federated Learning Framework for On-device Anomaly Data Detection | Tuo Zhang, Chaoyang He, Tianhao Ma, Lei Gao, Mark Ma, Salman Avestimehr | 2021-06-15 | arXiv | https://github.com/FedML-AI/FedIoT | https://arxiv.org/abs/2106.07976 |
| 560 | Federated Hyperparameter Tuning: Challenges, Baselines, and Connections to Weight-Sharing | Mikhail Khodak, Renbo Tu, Tian Li, Liam Li, Maria-Florina Balcan, Virginia Smith, Ameet Talwalkar | 2021-06-08 | NeurIPS 2021 Poster | https://github.com/mkhodak/fedex | http://arxiv.org/abs/2106.04502v2 |
| 561 | FedBABU: Towards Enhanced Representation for Federated Image Classification | Jaehoon Oh, Sangmook Kim, Se-Young Yun | 2021-06-04 | ICLR 2022 Poster | https://github.com/jhoon-oh/FedBABU | http://arxiv.org/abs/2106.06042v3 |
| 562 | SpreadGNN: Serverless Multi-task Federated Learning for Graph Neural Networks | Chaoyang He, Emir Ceyani, Keshav Balasubramanian, Murali Annavaram, Salman Avestimehr | 2021-06-04 | arXiv | https://github.com/FedML-AI/SpreadGNN | https://arxiv.org/abs/2106.02743 |
| 563 | PFA: Privacy-preserving Federated Adaptation for Effective Model Personalization | Bingyan Liu, Yao Guo, Xiangqun Chen | 2021-06 | WWW '21: Proceedings of the Web Conference 2021 | https://github.com/lebyni/PFA | https://dl.acm.org/doi/10.1145/3442381.3449847 |
| 564 | HyFed: A Hybrid Federated Framework for Privacy-preserving Machine Learning | Reza Nasirigerdeh, Reihaneh Torkzadehmahani, Julian O. Matschinske, Jan Baumbach, Daniel Rueckert, Georgios Kaissis | 2021-05-21 | arXiv | https://github.com/tum-aimed/hyfed | https://arxiv.org/abs/2105.10545 |
| 565 | A Privacy-Preserving Approach to Extraction of Personal Information through Automatic Annotation and Federated Learning | Rajitha Hathurusinghe, Isar Nejadgholi, Miodrag Bolic | 2021-05-19 | arXiv | https://github.com/ratmcu/wikipiifed | https://arxiv.org/abs/2105.09198 |
| 566 | DRIVE: One-bit Distributed Mean Estimation | Shay Vargaftik, Ran Ben Basat, Amit Portnoy, Gal Mendelson, Yaniv Ben-Itzhak, Michael Mitzenmacher | 2021-05-18 | NeurIPS 2021 Poster | https://github.com/amitport/DRIVE-One-bit-Distributed-Mean-Estimation | http://arxiv.org/abs/2105.08339v5 |
| 567 | OpenFL: An open-source framework for Federated Learning | G. Anthony Reina, Alexey Gruzdev, Patrick Foley, Olga Perepelkina, Mansi Sharma, Igor Davidyuk, Ilya Trushkin, Maksim Radionov, Aleksandr Mokrov, Dmitry Agapov, Jason Martin, Brandon Edwards, Micah J. Sheller, Sarthak Pati, Prakash Narayana Moorthy, Hans Shih-Han Wang, Prashant Shah, Spyridon Bakas | 2021-05-13 | arXiv | https://github.com/intel/openfl | https://arxiv.org/abs/2105.06413 |
| 568 | Federated Learning with Fair Averaging | Zheng Wang, Xiaoliang Fan, Jianzhong Qi, Chenglu Wen, Cheng Wang, Rongshan Yu | 2021-04-30 | IJCAI | https://github.com/WwZzz/easyFL | https://doi.org/10.24963/ijcai.2021/223 |
| 569 | FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks | Chaoyang He, Keshav Balasubramanian, Emir Ceyani, Carl Yang, Han Xie, Lichao Sun, Lifang He, Liangwei Yang, Philip S. Yu, Yu Rong, Peilin Zhao, Junzhou Huang, Murali Annavaram, Salman Avestimehr | 2021-04-14 | arXiv | https://github.com/FedML-AI/FedGraphNN | https://arxiv.org/abs/2104.07145 |
| 570 | Artifact: Opportunistic Federated Learning: An Exploration of Egocentric Collaboration for Pervasive Computing Applications | Sangsu Lee, Xi Zheng, Jie Hua, Haris Vikalo, Christine Julien | 2021-03-22 | 2021 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops) | https://github.com/UT-MPC/swarm | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9431012 |
| 571 | FedDG: Federated Domain Generalization on Medical Image Segmentation via Episodic Learning in Continuous Frequency Space | Quande Liu, Cheng Chen, Jing Qin, Qi Dou, Pheng-Ann Heng | 2021-03-10 | 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | https://github.com/liuquande/FedDG-ELCFS | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9577482 |
| 572 | FedDR -- Randomized Douglas-Rachford Splitting Algorithms for Nonconvex Federated Composite Optimization | Quoc Tran-Dinh, Nhan H. Pham, Dzung T. Phan, Lam M. Nguyen | 2021-03-05 | NeurIPs 2021 | https://github.com/unc-optimization/FedDR | http://arxiv.org/abs/2103.03452v3 |
| 573 | Multi-institutional Collaborations for Improving Deep Learning-based Magnetic Resonance Image Reconstruction Using Federated Learning | Pengfei Guo, Puyang Wang, Jinyuan Zhou, Shanshan Jiang, Vishal M. Patel | 2021-03-03 | 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | https://github.com/guopengf/FL-MRCM | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9578476 |
| 574 | One-Bit Over-the-Air Aggregation for Communication-Efficient Federated Edge Learning | Guangxu Zhu, Yuqing Du, Deniz Gündüz, Kaibin Huang | 2021-03-01 | GLOBECOM 2020 - 2020 IEEE Global Communications Conference | https://github.com/BornHater/One-bit-over-the-air-computation | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9322334 |
| 575 | FedBN: Federated Learning on Non-IID Features via Local Batch Normalization | Xiaoxiao Li, Meirui Jiang, Xiaofei Zhang, Michael Kamp, Qi Dou | 2021-02-15 | ICLR | https://github.com/med-air/FedBN | https://openreview.net/forum?id=6YEQUn0QICG |
| 576 | Federated Deep AUC Maximization for Heterogeneous Data with a Constant Communication Complexity | Zhuoning Yuan, Zhishuai Guo, Yi Xu, Yiming Ying, Tianbao Yang | 2021-02-09 | International Conference on Machine Learning (ICML 2021) | https://github.com/Optimization-AI/ICML2021_FedDeepAUC_CODASCA | http://arxiv.org/abs/2102.04635v3 |
| 577 | Federated Reconstruction: Partially Local Federated Learning | Karan Singhal, Hakim Sidahmed, Zachary Garrett, Shanshan Wu, J Keith Rush, Sushant Prakash | 2021-02-05 | NeurIPS | https://github.com/google-research/federated/tree/master/reconstruction | https://proceedings.neurips.cc/paper/2021/hash/5d44a2b0d85aa1a4dd3f218be6422c66-Abstract.html |
| 578 | Federated Multi-Armed Bandits | Chengshuai Shi, Cong Shen | 2021-01-28 | arXiv | https://github.com/ShenGroup/FMAB | http://arxiv.org/abs/2101.12204v2 |
| 579 | Dopamine: Differentially Private Federated Learning on Medical Data | Mohammad Malekzadeh, Burak Hasircioglu, Nitish Mital, Kunal Katarya, Mehmet Emre Ozfatura, Deniz Gündüz | 2021-01-27 | arXiv | https://github.com/ipc-lab/private-ml-for-health | https://arxiv.org/abs/2101.11693 |
| 580 | WAFFLE: Watermarking in Federated Learning | Buse G. A. Tekgul, Yuxi Xia, Samuel Marchal, N. Asokan | 2021-01-01 | 2021 40th International Symposium on Reliable Distributed Systems (SRDS) | https://github.com/ssg-research/WAFFLE | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9603498 |
| 581 | Soteria: Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective | Jingwei Sun, Ang Li, Binghui Wang, Huanrui Yang, Hai Li, Yiran Chen | 2021-01-01 | 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | https://github.com/jeremy313/Soteria | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9578192 |
| 582 | Perception Poisoning Attacks in Federated Learning | Ka Ho Chow, Ling Liu | 2021-01-01 | 2021 Third IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA) | https://github.com/git-disl/Perception-Poisoning | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9750251 |
| 583 | Model-sharing Games: Analyzing Federated Learning Under Voluntary Participation | Kate Donahue, Jon M. Kleinberg | 2021-01-01 | arXiv | https://github.com/kpdonahue/model_sharing_games | https://arxiv.org/abs/2010.00753 |
| 584 | Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms | Maruan Al-Shedivat, Jennifer Gillenwater, Eric P. Xing, Afshin Rostamizadeh | 2021-01-01 | arXiv | https://github.com/alshedivat/fedpa | https://arxiv.org/abs/2010.05273 |
| 585 | Federated Semi-Supervised Learning with Inter-Client Consistency & Disjoint Learning | Wonyong Jeong, Jaehong Yoon, Eunho Yang, Sung Ju Hwang | 2021-01-01 | ICLR | https://github.com/wyjeong/FedMatch | https://openreview.net/forum?id=ce6CFXBh30h |
| 586 | From Gradient Leakage To Adversarial Attacks In Federated Learning | Jia Qi Lim, Chee Seng Chan | 2021-01-01 | 2021 IEEE International Conference on Image Processing (ICIP) | https://github.com/Jiaqi0602/adversarial-attack-from-leakage/ | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9506589 |
| 587 | Federated Continual Learning with Weighted Inter-client Transfer | Jaehong Yoon, Wonyong Jeong, Giwoong Lee, Eunho Yang, Sung Ju Hwang | 2021-01-01 | ICML | https://github.com/wyjeong/FedWeIT | http://proceedings.mlr.press/v139/yoon21b.html |
| 588 | FedMAX: Mitigating Activation Divergence for Accurate and Communication-Efficient Federated Learning | Wei Chen, Kartikeya Bhardwaj, Radu Marculescu | 2021-01-01 | ECML/PKDD | https://github.com/weichennone/FedMAX | https://doi.org/10.1007/978-3-030-67661-2_21 |
| 589 | FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning | Hong-You Chen, Wei-Lun Chao | 2021-01-01 | ICLR | https://github.com/hongyouc/FedBE | https://openreview.net/forum?id=dgtpE6gKjHn |
| 590 | DeepReduce: A Sparse-tensor Communication Framework for Federated Deep Learning | Hang Xu, Kelly Kostopoulou, Aritra Dutta, Xin Li, Alexandros Ntoulas, Panos Kalnis | 2021-01-01 | NeurIPS | https://github.com/hangxu0304/DeepReduce | https://proceedings.neurips.cc/paper/2021/hash/b0ab42fcb7133122b38521d13da7120b-Abstract.html |
| 591 | A Joint Learning and Communications Framework for Federated Learning Over Wireless Networks | Mingzhe Chen, Zhaohui Yang, Walid Saad, Changchuan Yin, H. Vincent Poor, Shuguang Cui | 2021-01-01 | IEEE Transactions on Wireless Communications | https://github.com/mzchen0/Wireless-FL | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9210812 |
| 592 | A Federated Multigraph Integration Approach for Connectional Brain Template Learning | Hizir Can Bayram, Islem Rekik | 2021-01-01 | ML-CDS@MICCAI | https://github.com/basiralab/Fed-CBT | https://doi.org/10.1007/978-3-030-89847-2_4 |
| 593 | Federated Block Coordinate Descent Scheme for Learning Global and Personalized Models | Ruiyuan Wu, Anna Scaglione, Hoi-To Wai, Nurullah Karakoç, Kari Hreinsson, Wing-Kin Ma | 2021-01-01 | arXiv | https://github.com/REIYANG/FedBCD | https://arxiv.org/abs/2012.13900 |
| 594 | Soft-Label Dataset Distillation and Text Dataset Distillation | I. Sucholutsky, M. Schonlau | 2021 | 2021 International Joint Conference on Neural Networks (IJCNN) | https://github.com/ilia10000/dataset-distillation | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9533769 |
| 595 | Time- and Computation-Efficient Data Localization at Vehicular Networks’ Edge | R. Duvignau, B. Havers, V. Gulisano, M. Papatriantafilou | 2021 | IEEE Access | https://github.com/dcs-chalmers/dataloc_vn | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9562541 |
| 596 | Use Procedural Noise to Achieve Backdoor Attack | X. Chen, Y. Ma, S. Lu | 2021 | IEEE Access | https://github.com/928082786/pnoiseattack | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9529206 |
| 597 | Privacy-Net: An Adversarial Approach for Identity-Obfuscated Segmentation of Medical Images | B. N. Kim, J. Dolz, P. -M. Jodoin, C. Desrosiers | 2021 | IEEE Transactions on Medical Imaging | https://github.com/bachkimn/Privacy-Net-An-Adversarial-Approach-forIdentity-Obfuscated-Segmentation-of-MedicalImages | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9376890 |
| 598 | Incentive-Driven Long-term Optimization for Edge Learning by Hierarchical Reinforcement Mechanism | Y. Liu, L. Wu, Y. Zhan, S. Guo, Z. Hong | 2021 | 2021 IEEE 41st International Conference on Distributed Computing Systems (ICDCS) | https://github.com/Joey61Liuyi/Chiron | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9546525 |
| 599 | Federated Composite Optimization | Honglin Yuan, Manzil Zaheer, Sashank Reddi | 2020-11-17 | arXiv | https://github.com/hongliny/FCO-ICML21 | http://arxiv.org/abs/2011.08474v3 |
| 600 | End-to-End Evaluation of Federated Learning and Split Learning for Internet of Things | Yansong Gao, Minki Kim, Sharif Abuadbba, Yeonjae Kim, Chandra Thapa, Kyuyeon Kim, Seyit Ahmet Çamtepe, Hyoungshick Kim, Surya Nepal | 2020-09-01 | 2020 International Symposium on Reliable Distributed Systems (SRDS) | https://github.com/Minki-Kim95/Federated-Learning-and-Split-Learning-with-raspberry-pi | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9252066 |
| 601 | Fed-Sim: Federated Simulation for Medical Imaging | Daiqing Li, Amlan Kar, Nishant Ravikumar, Alejandro F Frangi, Sanja Fidler | 2020-09-01 | arXiv | https://nv-tlabs.github.io/fed-sim/ | http://arxiv.org/abs/2009.00668v1 |
| 602 | Learn distributed GAN with Temporary Discriminators | Hui Qu, Yikai Zhang, Qi Chang, Zhennan Yan, Chao Chen, Dimitris Metaxas | 2020-07-17 | arXiv | https://github.com/huiqu18/TDGAN-PyTorch | http://arxiv.org/abs/2007.09221v1 |
| 603 | Federated Learning with Matched Averaging | Hongyi Wang, Mikhail Yurochkin, Yuekai Sun, Dimitris S. Papailiopoulos, Yasaman Khazaeni | 2020-02-15 | ICLR | https://github.com/IBM/FedMA | https://openreview.net/forum?id=BkluqlSFDS |
| 604 | Think Locally, Act Globally: Federated Learning with Local and Global Representations | Paul Pu Liang, Terrance Liu, Liu Ziyin, Nicholas B. Allen, Randy P. Auerbach, David Brent, Ruslan Salakhutdinov, Louis-Philippe Morency | 2020-01-06 | arXiv | https://github.com/pliang279/LG-FedAvg | http://arxiv.org/abs/2001.01523 |
| 605 | Fair Resource Allocation in Federated Learning | Tian Li, Maziar Sanjabi, Ahmad Beirami, Virginia Smith | 2020-01-01 | ICLR | https://github.com/litian96/fair_flearn | https://openreview.net/forum?id=ByexElSYDr |
| 606 | DeepCABAC: A Universal Compression Algorithm for Deep Neural Networks | S. Wiedemann, H. Kirchhoffer, S. Matlage, P. Haase, A. Marban, T. Marinč, D. Neumann, T. Nguyen, H. Schwarz, T. Wiegand, D. Marpe, W. Samek | 2020 | IEEE Journal of Selected Topics in Signal Processing | https://github.com/fraunhoferhhi/DeepCABAC | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8970294 |
| 607 | Analyzing Federated Learning through an Adversarial Lens | Arjun Nitin Bhagoji, Supriyo Chakraborty, Prateek Mittal, Seraphin B. Calo | 2019-01-01 | arXiv | https://github.com/inspire-group/ModelPoisoning | http://arxiv.org/abs/1811.12470 |
| 608 | Mitigating Sybils in Federated Learning Poisoning | Clement Fung, Chris J. M. Yoon, Ivan Beschastnikh | 2018-08-14 | arXiv | https://github.com/DistributedML/FoolsGold | http://arxiv.org/abs/1808.04866 |
| 609 | Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training | Yujun Lin, Song Han, Huizi Mao, Yu Wang, William J. Dally | 2017-12-05 | ICLR 2018 | https://github.com/synxlin/deep-gradient-compression | http://arxiv.org/abs/1712.01887v3 |
| 610 | Accumulative Poisoning Attacks on Real-time Data | Tianyu Pang, Xiao Yang, Yinpeng Dong, Hang Su, Jun Zhu | nan | NeurIPS 2021 Poster | https://github.com/ShawnXYang/AccumulativeAttack | https://openreview.net/pdf/d65209823dabc51160d13fcccbd40f453b80b4d3.pdf |
| 611 | An Analysis of Transferability in Network Intrusion Detection using Distributed Deep Learning | Shreya Ghosh, Abu Shafin Mohammad Mahdee Jameel, Aly El Gamal | nan | Submitted to Tiny Papers @ ICLR 2023 | https://github.com/ghosh64/fedlearn | https://openreview.net/pdf/18ec29f439f4abc1f075d093d49fb13189dc7953.pdf |
| 612 | FedFA: Federated Feature Augmentation | Tianfei Zhou, Ender Konukoglu | nan | ICLR 2023 poster | https://github.com/tfzhou/FedFA | https://openreview.net/pdf/83d761ced643dbc84793236240410a72064dcf32.pdf |
| 613 | FedGS: Federate Graph-based Sampling with Arbitrary Client Availability | Zheng Wang, Xiaoliang Fan, Jianzhong Qi, Haibing Jin, peizhen yang, Siqi Shen, Cheng Wang | nan | OpenReview | https://github.com/WwZzz/FedGS | https://arxiv.org/pdf/2211.13975.pdf |
| 614 | Federated Blood Supply Chain Demand Forecasting: A Case Study | Hanzhe Wei, Na Li, Jiajun Wu, Jiayu Zhou, STEVE DREW | nan | FL4Data-Mining Poster | https://github.com/denoslab/fl-blood-supply-chain | https://openreview.net/pdf/a9db7e2ac081d21563af2ec030b56617adea61c6.pdf |
| 615 | Generative Models for Effective ML on Private, Decentralized Datasets | Sean Augenstein, H. Brendan McMahan, Daniel Ramage, Swaroop Ramaswamy, Peter Kairouz, Mingqing Chen, Rajiv Mathews, Blaise Aguera y Arcas | nan | OpenReview | https://github.com/tensorflow/federated/tree/master/tensorflow_federated/python/research/gans | https://openreview.net/pdf/ec8b5bcb57ec7ce967ce19be3e0aa3389526aca0.pdf |
| 616 | Gradient Driven Rewards to Guarantee Fairness in Collaborative Machine Learning | Xinyi Xu, Lingjuan Lyu, Xingjun Ma, Chenglin Miao, Chuan-Sheng Foo, Bryan Kian Hsiang Low | nan | NeurIPS 2021 Poster | https://github.com/XinyiYS/Gradient-Driven-Rewards-to-Guarantee-Fairness-in-Collaborative-Machine-Learning | https://openreview.net/pdf/a0b90251635339995dc84267af94b013b0da36b0.pdf |
| 617 | Gradient Inversion with Generative Image Prior | Jinwoo Jeon, Jaechang Kim, Kangwook Lee, Sewoong Oh, Jungseul Ok | nan | NeurIPS 2021 Poster | https://github.com/ml-postech/gradient-inversion-generative-image-prior | https://openreview.net/pdf/a2d4097596388e4a3608a53c05551e2213298718.pdf |
| 618 | MocoSFL: enabling cross-client collaborative self-supervised learning | Jingtao Li, Lingjuan Lyu, Daisuke Iso, Chaitali Chakrabarti, Michael Spranger | nan | ICLR 2023 notable top 5% | https://github.com/SonyAI/MocoSFL | https://openreview.net/pdf/e7d98a4942f9fa3e0236bec53218b97e0792f3ee.pdf |
| 619 | Moshpit SGD: Communication-Efficient Decentralized Training on Heterogeneous Unreliable Devices | Max Ryabinin, Eduard Gorbunov, Vsevolod Plokhotnyuk, Gennady Pekhimenko | nan | NeurIPS 2021 Poster | https://github.com/yandex-research/moshpit-sgd | https://openreview.net/pdf/52ba0e1c4ac8204231555ba0fe03623d12981dd4.pdf |
| 620 | On Federated Learning of Deep Networks from Non-IID Data: Parameter Divergence and the Effects of Hyperparametric Methods | Heejae Kim, Taewoo Kim, Chan-Hyun Youn | nan | OpenReview | https://github.com/fl-noniid/fl-noniid | https://openreview.net/pdf/5e77d730063a01ed6a3cd0b0b51e689011736107.pdf |
| 621 | On the Convergence of FedAvg on Non-IID Data | Xiang Li, Kaixuan Huang, Wenhao Yang, Shusen Wang, Zhihua Zhang | nan | OpenReview | https://github.com/lx10077/fedavgpy | https://openreview.net/pdf/dcd68da80bc99678b1254ec0b4d49dee872c7898.pdf |
| 622 | Preserved central model for faster bidirectional compression in distributed settings | Constantin Philippenko, Aymeric Dieuleveut | nan | NeurIPS 2021 Poster | https://github.com/philipco/mcm-bidirectional-compression | https://openreview.net/pdf/5c4a6778e03d94596f6007c49682bea07081ba34.pdf |
| 623 | Qu-ANTI-zation: Exploiting Quantization Artifacts for Achieving Adversarial Outcomes | Sanghyun Hong, Michael-Andrei Panaitescu-Liess, Yigitcan Kaya, Tudor Dumitras | nan | NeurIPS 2021 Poster | https://github.com/Secure-AI-Systems-Group/Qu-ANTI-zation | https://openreview.net/pdf/d99b499610c11e58db2b8e2b8b421fbd7ec493a8.pdf |
| 624 | R-GAP: Recursive Gradient Attack on Privacy | Junyi Zhu, Matthew B. Blaschko | nan | ICLR 2021 Poster | https://github.com/JunyiZhu-AI/R-GAP | https://openreview.net/pdf/943e8621d1ff1fb8b9daa8cc68876c327966099c.pdf |
| 625 | Robust and differentially private mean estimation | Xiyang Liu, Weihao Kong, Sham M. Kakade, Sewoong Oh | nan | NeurIPS 2021 Poster | https://github.com/SewoongLab/robust_dp | https://openreview.net/pdf/89291f9e9687066d4c09fe7e4a2a42ca85637a3d.pdf |
| 626 | Validation Free and Replication Robust Volume-based Data Valuation | Xinyi Xu, Zhaoxuan Wu, Chuan-Sheng Foo, Bryan Kian Hsiang Low | nan | NeurIPS 2021 Poster | https://github.com/ZhaoxuanWu/VolumeBased-DataValuation | https://openreview.net/pdf/48155495ba2187295435b80d88dadf92ed45d9ce.pdf |
