Federated Learning

Dual Personalization on Federated Recommendation IJCAI 2023 DynaFed: Tackling Client Data Heterogeneity With Global Dynamics CVPR 2023 Dynamic Personalized Federated Learning with Adaptive Differential Privacy NeurIPS 2023 Echo of Neighbors: Privacy Amplification for Personalized Private Federated Learning with Shuffle Model AAAI 2023 Effective passive membership inference attacks in federated learning against overparameterized models ICLR 2023 Efficient and Light-Weight Federated Learning via Asynchronous Distributed Dropout AISTATS 2023 Efficient Distribution Similarity Identification in Clustered Federated Learning via Principal Angles between Client Data Subspaces AAAI 2023 Efficient Federated Domain Translation ICLR 2023 Efficient Model Personalization in Federated Learning via Client-Specific Prompt Generation ICCV 2023 Efficient Personalized Federated Learning via Sparse Model-Adaptation ICML 2023 Efficient Training of Large-Scale Industrial Fault Diagnostic Models through Federated Opportunistic Block Dropout AAAI 2023 Elastic Aggregation for Federated Optimization CVPR 2023 Eliminating Domain Bias for Federated Learning in Representation Space NeurIPS 2023 Empirical Study of Federated Unlearning: Efficiency and Effectiveness ACML 2023 Enhancing Privacy Preservation in Federated Learning via Learning Rate Perturbation ICCV 2023 Epidemic Learning: Boosting Decentralized Learning with Randomized Communication NeurIPS 2023 EPISODE: Episodic Gradient Clipping with Periodic Resampled Corrections for Federated Learning with Heterogeneous Data ICLR 2023 Every Parameter Matters: Ensuring the Convergence of Federated Learning with Dynamic Heterogeneous Models Reduction NeurIPS 2023 EvoFed: Leveraging Evolutionary Strategies for Communication-Efficient Federated Learning NeurIPS 2023 FairFed: Enabling Group Fairness in Federated Learning AAAI 2023 Fair yet Asymptotically Equal Collaborative Learning ICML 2023 Faster federated optimization under second-order similarity ICLR 2023 Fast Federated Machine Unlearning with Nonlinear Functional Theory ICML 2023 Fast Heterogeneous Federated Learning with Hybrid Client Selection UAI 2023 FedABC: Targeting Fair Competition in Personalized Federated Learning AAAI 2023