heterogeneous client

FedPHA: Federated Prompt Learning for Heterogeneous Client Adaptation ICML 2025 One-Shot Heterogeneous Federated Learning with Local Model-Guided Diffusion Models ICML 2025 Towards Robust and Efficient Federated Low-Rank Adaptation with Heterogeneous Clients ACL 2025 Federated Linear Contextual Bandits with Heterogeneous Clients AISTATS 2024 FedLMT: Tackling System Heterogeneity of Federated Learning via Low-Rank Model Training with Theoretical Guarantees ICML 2024 MH-pFLID: Model Heterogeneous personalized Federated Learning via Injection and Distillation for Medical Data Analysis ICML 2024 Recurrent Early Exits for Federated Learning with Heterogeneous Clients ICML 2024 Resource-Aware Federated Self-Supervised Learning with Global Class Representations NeurIPS 2024 A General Theory for Federated Optimization with Asynchronous and Heterogeneous Clients Updates JMLR 2023 Beyond ADMM: A Unified Client-Variance-Reduced Adaptive Federated Learning Framework AAAI 2023 ScaleFL: Resource-Adaptive Federated Learning With Heterogeneous Clients CVPR 2023 FedProto: Federated Prototype Learning across Heterogeneous Clients AAAI 2022 Federated Learning under Arbitrary Communication Patterns ICML 2021 HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients ICLR 2021