data heterogeneity

DPFL: Decentralized Personalized Federated Learning AISTATS 2025 DUET: Decentralized Bilevel Optimization without Lower-Level Strong Convexity ICLR 2025 EFSkip: A New Error Feedback with Linear Speedup for Compressed Federated Learning with Arbitrary Data Heterogeneity AAAI 2025 Enhancing Federated Domain Adaptation with Multi-Domain Prototype-Based Federated Fine-Tuning ICLR 2025 Enhancing the Performance of Global Model by Improving the Adaptability of Local Models in Federated Learning IJCAI 2025 FAST: A Lightweight Mechanism Unleashing Arbitrary Client Participation in Federated Learning IJCAI 2025 FDPT: Federated Discrete Prompt Tuning for Black-Box Visual-Language Models ICCV 2025 FedAWA: Adaptive Optimization of Aggregation Weights in Federated Learning Using Client Vectors CVPR 2025 FedBiP: Heterogeneous One-Shot Federated Learning with Personalized Latent Diffusion Models CVPR 2025 FedDifRC: Unlocking the Potential of Text-to-Image Diffusion Models in Heterogeneous Federated Learning ICCV 2025 Federated Continual Instruction Tuning ICCV 2025 Federated Disentangled Tuning with Textual Prior Decoupling and Visual Dynamic Adaptation ICML 2025 Federated Learning with Sample-level Client Drift Mitigation AAAI 2025 FedWSQ: Efficient Federated Learning with Weight Standardization and Distribution-Aware Non-Uniform Quantization ICCV 2025 FedXDS: Leveraging Model Attribution Methods to counteract Data Heterogeneity in Federated Learning ICCV 2025 FLSeg: Enhancing Privacy and Robustness in Federated Learning under Heterogeneous Data via Model Segmentation ICCV 2025 Geometric Knowledge-Guided Localized Global Distribution Alignment for Federated Learning CVPR 2025 How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? AAAI 2025 Inconsistency-Based Federated Active Learning IJCAI 2025 Mind the Gap: Confidence Discrepancy Can Guide Federated Semi-Supervised Learning Across Pseudo-Mismatch CVPR 2025 MLLM-LLaVA-FL: Multimodal Large Language Model Assisted Federated Learning WACV 2025 Multimodal Fusion Using Multi-View Domains for Data Heterogeneity in Federated Learning AAAI 2025 MultiSFL: Towards Accurate Split Federated Learning via Multi-Model Aggregation and Knowledge Replay AAAI 2025 Navigating Heterogeneity and Privacy in One-Shot Federated Learning with Diffusion Models WACV 2025 One Arrow, Two Hawks: Sharpness-aware Minimization for Federated Learning via Global Model Trajectory ICML 2025