client-server architecture

Safely Learning with Private Data: A Federated Learning Framework for Large Language Model EMNLP 2024 Federated Cross Learning for Medical Image Segmentation MIDL 2023 Federated Learning for Commercial Image Sources WACV 2023 Federated Learning from Small Datasets ICLR 2023 Federated Learning with Manifold Regularization and Normalized Update Reaggregation NeurIPS 2023 FedSpeed: Larger Local Interval, Less Communication Round, and Higher Generalization Accuracy ICLR 2023 Flow: Per-instance Personalized Federated Learning NeurIPS 2023 GPFL: Simultaneously Learning Global and Personalized Feature Information for Personalized Federated Learning ICCV 2023 Machine Unlearning of Federated Clusters ICLR 2023 Personalized Federated Learning under Mixture of Distributions ICML 2023 Robust Heterogeneous Federated Learning under Data Corruption ICCV 2023 DAdaQuant: Doubly-adaptive quantization for communication-efficient Federated Learning ICML 2022 Differentially Private Federated Learning on Heterogeneous Data AISTATS 2022 Federated Learning with Buffered Asynchronous Aggregation AISTATS 2022 Federated Learning With Position-Aware Neurons CVPR 2022 Federated Submodel Optimization for Hot and Cold Data Features NeurIPS 2022 HarmoFL: Harmonizing Local and Global Drifts in Federated Learning on Heterogeneous Medical Images AAAI 2022 Is Your Data Relevant?: Dynamic Selection of Relevant Data for Federated Learning AAAI 2022 Orchestra: Unsupervised Federated Learning via Globally Consistent Clustering ICML 2022 Self-Aware Personalized Federated Learning NeurIPS 2022 Addressing Algorithmic Disparity and Performance Inconsistency in Federated Learning NeurIPS 2021 Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms ICLR 2021 QuPeD: Quantized Personalization via Distillation with Applications to Federated Learning NeurIPS 2021 Agnostic Federated Learning ICML 2019