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Federated Learning

497 directly classified papers

Papers per year

Papers

HaCore: Efficient Coreset Construction with Locality Sensitive Hashing for Vertical Federated Learning AAAI 2025
Personalized Label Inference Attack in Federated Transfer Learning via Contrastive Meta Learning AAAI 2025
Reputation-aware Revenue Allocation for Auction-based Federated Learning AAAI 2025
Towards Privacy-Preserving Split Learning for ControlNet WACV 2025
Defending Against Sophisticated Poisoning Attacks with RL-based Aggregation in Federated Learning AAAI 2025
Efficient Federated Learning via Clients-to-Server Knowledge Distillation (Student Abstract) AAAI 2025
Decentralized Low-Rank Fine-Tuning of Large Language Models ACL 2025
PPIDSG: A Privacy-Preserving Image Distribution Sharing Scheme with GAN in Federated Learning AAAI 2024
Federated Ensemble-Directed Offline Reinforcement Learning NIPS 2024
Sketching for Distributed Deep Learning: A Sharper Analysis NIPS 2024
Ferrari: Federated Feature Unlearning via Optimizing Feature Sensitivity NIPS 2024
FedASMU: Efficient Asynchronous Federated Learning with Dynamic Staleness-Aware Model Update AAAI 2024
FedLPA: One-shot Federated Learning with Layer-Wise Posterior Aggregation NIPS 2024
Don't Compress Gradients in Random Reshuffling: Compress Gradient Differences NIPS 2024
DIMAT: Decentralized Iterative Merging-And-Training for Deep Learning Models CVPR 2024
Language-Guided Transformer for Federated Multi-Label Classification AAAI 2024
Mixed-Precision Quantization for Federated Learning on Resource-Constrained Heterogeneous Devices CVPR 2024
Federated X-armed Bandit AAAI 2024
Open-Vocabulary Federated Learning with Multimodal Prototyping NAACL 2024
EMGAN: Early-Mix-GAN on Extracting Server-Side Model in Split Federated Learning AAAI 2024
FedNS: A Fast Sketching Newton-Type Algorithm for Federated Learning AAAI 2024
UFDA: Universal Federated Domain Adaptation with Practical Assumptions AAAI 2024
Federated Learning with Extremely Noisy Clients via Negative Distillation AAAI 2024
Federated Linear Contextual Bandits with Heterogeneous Clients AISTATS 2024
Minimizing Layerwise Activation Norm Improves Generalization in Federated Learning WACV 2024