federated averaging

Class-Wise Federated Averaging for Efficient Personalization ICCV 2025 Debiasing Federated Learning with Correlated Client Participation ICLR 2025 Global Group Fairness in Federated Learning via Function Tracking AISTATS 2025 On the Power of Adaptive Weighted Aggregation in Heterogeneous Federated Learning and Beyond AISTATS 2025 Refined Analysis of Constant Step Size Federated Averaging and Federated Richardson-Romberg Extrapolation AISTATS 2025 A Lightweight Method for Tackling Unknown Participation Statistics in Federated Averaging ICLR 2024 Communication-Efficient Federated Learning With Data and Client Heterogeneity AISTATS 2024 On the Role of Server Momentum in Federated Learning AAAI 2024 Understanding Convergence and Generalization in Federated Learning through Feature Learning Theory ICLR 2024 Does Learning from Decentralized Non-IID Unlabeled Data Benefit from Self Supervision? ICLR 2023 Federated Asymptotics: a model to compare federated learning algorithms AISTATS 2023 FedExP: Speeding Up Federated Averaging via Extrapolation ICLR 2023 On the Convergence of Federated Averaging with Cyclic Client Participation ICML 2023 A Unified Analysis of Federated Learning with Arbitrary Client Participation NeurIPS 2022 FedAvg with Fine Tuning: Local Updates Lead to Representation Learning NeurIPS 2022 FedBABU: Toward Enhanced Representation for Federated Image Classification ICLR 2022 Iterated Vector Fields and Conservatism, with Applications to Federated Learning ALT 2022 Minibatch vs Local SGD with Shuffling: Tight Convergence Bounds and Beyond ICLR 2022 Sharp Bounds for Federated Averaging (Local SGD) and Continuous Perspective AISTATS 2022 Adaptive Federated Optimization ICLR 2021 Communication-Efficient Agnostic Federated Averaging Interspeech 2021 A Unified Theory of Decentralized SGD with Changing Topology and Local Updates ICML 2020 Distributionally Robust Federated Averaging NeurIPS 2020 On the Convergence of FedAvg on Non-IID Data ICLR 2020