federated learning

Sharp Bounds for Sequential Federated Learning on Heterogeneous Data JMLR 2025 Sibai: A Few-Shot Meta-Classifier for Poisoning Detection in Federated Learning ICCV 2025 Simple Yet Effective: Extracting Private Data Across Clients in Federated Fine-Tuning of Large Language Models IJCNLP 2025 Soft Separation and Distillation: Toward Global Uniformity in Federated Unsupervised Learning ICCV 2025 Some Targets Are Harder to Identify than Others: Quantifying the Target-dependent Membership Leakage AISTATS 2025 SparsyFed: Sparse Adaptive Federated Learning ICLR 2025 Splitting with Importance-aware Updating for Heterogeneous Federated Learning with Large Language Models ICML 2025 SPMC: Self-Purifying Federated Backdoor Defense via Margin Contribution ICML 2025 Stealthy Backdoor Attack in Federated Learning via Adaptive Layer-wise Gradient Alignment ICCV 2025 Subgraph Federated Learning for Local Generalization ICLR 2025 Subspace Constraint and Contribution Estimation for Heterogeneous Federated Learning CVPR 2025 Tackling Intertwined Data and Device Heterogeneities in Federated Learning with Unlimited Staleness AAAI 2025 Tensor-aggregated LoRA in Federated Fine-tuning ICCV 2025 The cost of local and global fairness in Federated Learning AISTATS 2025 Towards Federated Low-Rank Adaptation of Language Models with Rank Heterogeneity NAACL 2025 Towards Federated RLHF with Aggregated Client Preference for LLMs ICLR 2025 Towards Privacy-preserved Pre-training of Remote Sensing Foundation Models with Federated Mutual-guidance Learning ICCV 2025 Towards Privacy-Preserving Split Learning for ControlNet WACV 2025 Towards Robust and Efficient Federated Low-Rank Adaptation with Heterogeneous Clients ACL 2025 Towards Trustworthy Federated Learning with Untrusted Participants ICML 2025 TRAIL: Trust-Aware Client Scheduling for Semi-Decentralized Federated Learning AAAI 2025 TTA-FedDG: Leveraging Test-Time Adaptation to Address Federated Domain Generalization AAAI 2025 Unbiased Quantization of the L_1 Ball for Communication-Efficient Distributed Mean Estimation AISTATS 2025 Uncertainty-Based Extensible Codebook for Discrete Federated Learning in Heterogeneous Data Silos ICML 2025 Understanding the Impact of Client Heterogeneity on Ordinal Classification in Federated Medical Image Analysis MIDL 2025