Clients Collaborate: Flexible Differentially Private Federated Learning with Guaranteed Improvement of Utility-Privacy Trade-offby Yuecheng Li,…
FedImpro: Measuring and Improving Client Update in Federated Learningby Zhenheng Tang, Yonggang Zhang, Shaohuai Shi,…
FedMIA: An Effective Membership Inference Attack Exploiting “All for One” Principle in Federated Learningby Gongxi…
Blockchain-enabled Clustered and Scalable Federated Learning (BCS-FL) Framework in UAV Networksby Sana Hafeez, Lina Mohjazi,…
On the Convergence of Zeroth-Order Federated Tuning for Large Language Modelsby Zhenqing Ling, Daoyuan Chen,…
Federated Offline Reinforcement Learning: Collaborative Single-Policy Coverage Sufficesby Jiin Woo, Laixi Shi, Gauri Joshi, Yuejie…
Asynchronous Diffusion Learning with Agent Subsampling and Local Updatesby Elsa Rizk, Kun Yuan, Ali H.…
FedAA: A Reinforcement Learning Perspective on Adaptive Aggregation for Fair and Robust Federated Learningby Jialuo…
Flashback: Understanding and Mitigating Forgetting in Federated Learningby Mohammed Aljahdali, Ahmed M. Abdelmoniem, Marco Canini,…
Revisiting Early-Learning Regularization When Federated Learning Meets Noisy Labelsby Taehyeon Kim, Donggyu Kim, Se-Young YunFirst…