Federated Learning

Stabilized Proximal-Point Methods for Federated Optimization NeurIPS 2024 Stakeholder-oriented Decision Support for Auction-based Federated Learning IJCAI 2024 Stochastic Controlled Averaging for Federated Learning with Communication Compression ICLR 2024 Stochastic Smoothed Gradient Descent Ascent for Federated Minimax Optimization AISTATS 2024 Tackling the Data Heterogeneity in Asynchronous Federated Learning with Cached Update Calibration ICLR 2024 Taming Cross-Domain Representation Variance in Federated Prototype Learning with Heterogeneous Data Domains NeurIPS 2024 Text-Enhanced Data-free Approach for Federated Class-Incremental Learning CVPR 2024 The Power of Extrapolation in Federated Learning NeurIPS 2024 The Rise of Federated Intelligence: From Federated Foundation Models Toward Collective Intelligence IJCAI 2024 The Sample-Communication Complexity Trade-off in Federated Q-Learning NeurIPS 2024 Thinking Forward: Memory-Efficient Federated Finetuning of Language Models NeurIPS 2024 Think Twice Before Selection: Federated Evidential Active Learning for Medical Image Analysis with Domain Shifts CVPR 2024 Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting NeurIPS 2024 Towards Diverse Device Heterogeneous Federated Learning via Task Arithmetic Knowledge Integration NeurIPS 2024 Towards Efficient Replay in Federated Incremental Learning CVPR 2024 Towards Principled Representation Learning from Videos for Reinforcement Learning ICLR 2024 Towards the Robustness of Differentially Private Federated Learning AAAI 2024 TransFed: A Way To Epitomize Focal Modulation Using Transformer-Based Federated Learning WACV 2024 Understanding Convergence and Generalization in Federated Learning through Feature Learning Theory ICLR 2024 Understanding Generalization of Federated Learning via Stability: Heterogeneity Matters AISTATS 2024 Universal Sample Coding NeurIPS 2024 Unlearning during Learning: An Efficient Federated Machine Unlearning Method IJCAI 2024 VertiBench: Advancing Feature Distribution Diversity in Vertical Federated Learning Benchmarks ICLR 2024 Why Go Full? Elevating Federated Learning Through Partial Network Updates NeurIPS 2024 Would You Like Your Data to Be Trained? A User Controllable Recommendation Framework AAAI 2024