data heterogeneity

A Unified Convergence Analysis for Semi-Decentralized Learning: Sampled-to-Sampled vs. Sampled-to-All Communication AAAI 2026 DA-DFGAS:Differentiable Federated Graph Neural Architecture Search with Distribution-Aware Attentive Aggregation AAAI 2026 Data Heterogeneity and Forgotten Labels in Split Federated Learning AAAI 2026 DP-FedAdamW: An Efficient Optimizer for Differentially Private Federated Large Models CVPR 2026 Enhancing Visual Representation with Textual Semantics: Textual Semantics-Powered Prototypes for Heterogeneous Federated Learning CVPR 2026 FedAdamom: Adaptive Momentum for Improved Generalization in Federated Optimization CVPR 2026 FedCART: Tackling Long-Tailed Distributions in Federated Adversarial Training via Classifier Refinement CVPR 2026 FedEFC: Federated Learning Using Enhanced Forward Correction Against Noisy Labels WACV 2026 Federated EndoViT: Pretraining Vision Transformers via Federated Learning on Endoscopic Image Collections MIDL 2026 FedProxy: Federated Fine-Tuning of LLMs via Proxy SLMs and Heterogeneity-Aware Fusion ACL 2026 FedRG: Unleashing the Representation Geometry for Federated Learning with Noisy Clients CVPR 2026 Few-for-Many Personalized Federated Learning CVPR 2026 Guiding Diffusion Models with Fine-Grained Conditions and Semantics-Preserving Sampling for One-Shot Federated Learning CVPR 2026 One-Shot Federated Learning based on Random Feature Extractor UAI 2026 Personalized Image Privacy Advisors via Federated Daisy-Chaining WACV 2026 ProxyFL: A Proxy-Guided Framework for Federated Semi-Supervised Learning CVPR 2026 SMoFi: Step-wise Momentum Fusion for Split Federated Learning on Heterogeneous Data AAAI 2026 Tackling Resource-Constrained and Data-Heterogeneity in Federated Learning with Double-Weight Sparse Pack AAAI 2026 TOFA: Training-Free One-Shot Federated Adaptation for Vision-Language Models AAAI 2026 Who to Trust? Aggregating Client Predictions in Federated Distillation. UAI 2026 An Empirical Study of Federated Prompt Learning for Vision Language Model IJCAI 2025 Bad-PFL: Exploiting Backdoor Attacks against Personalized Federated Learning ICLR 2025 Client2Vec: Improving Federated Learning by Distribution Shifts Aware Client Indexing ICCV 2025 Communication-Efficient and Tensorized Federated Fine-Tuning of Large Language Models ACL 2025 Distributed Stochastic Bilevel Optimization: Improved Complexity and Heterogeneity Analysis JMLR 2025