Federated Learning

Bidirectional Contrastive Split Learning for Visual Question Answering AAAI 2024 BOBA: Byzantine-Robust Federated Learning with Label Skewness AISTATS 2024 Breaking Physical and Linguistic Borders: Multilingual Federated Prompt Tuning for Low-Resource Languages ICLR 2024 Bridging Gaps: Federated Multi-View Clustering in Heterogeneous Hybrid Views NeurIPS 2024 Byzantine-Robust Decentralized Learning via Remove-then-Clip Aggregation AAAI 2024 Byzantine Robustness and Partial Participation Can Be Achieved at Once: Just Clip Gradient Differences NeurIPS 2024 Calibrated One Round Federated Learning with Bayesian Inference in the Predictive Space AAAI 2024 Can LLMs get help from other LLMs without revealing private information? ACL 2024 Can Public Large Language Models Help Private Cross-device Federated Learning? NAACL 2024 Chronic Poisoning: Backdoor Attack against Split Learning AAAI 2024 Classifier Clustering and Feature Alignment for Federated Learning under Distributed Concept Drift NeurIPS 2024 CLIP-Guided Federated Learning on Heterogeneity and Long-Tailed Data AAAI 2024 Collaborative Learning across Heterogeneous Systems with Pre-Trained Models AAAI 2024 Collaborative Learning of Anomalies with Privacy (CLAP) for Unsupervised Video Anomaly Detection: A New Baseline CVPR 2024 Combating Data Imbalances in Federated Semi-supervised Learning with Dual Regulators AAAI 2024 Communication-Efficient Federated Group Distributionally Robust Optimization NeurIPS 2024 Communication-Efficient Federated Learning with Accelerated Client Gradient CVPR 2024 Communication-Efficient Federated Learning With Data and Client Heterogeneity AISTATS 2024 Communication-Efficient Federated Non-Linear Bandit Optimization ICLR 2024 Complementary Knowledge Distillation for Robust and Privacy-Preserving Model Serving in Vertical Federated Learning AAAI 2024 Compressed and distributed least-squares regression: convergence rates with applications to federated learning JMLR 2024 Compression with Exact Error Distribution for Federated Learning AISTATS 2024 Concealing Sensitive Samples against Gradient Leakage in Federated Learning AAAI 2024 Countering the Communication Bottleneck in Federated Learning: A Highly Efficient Zero-Order Optimization Technique JMLR 2024 Cross-Feature Contrastive Loss for Decentralized Deep Learning on Heterogeneous Data WACV 2024