← Learning Paradigms
Machine Learning › Learning Paradigms ›

Federated Learning

551 directly classified papers

Papers per year

Papers

Client2Vec: Improving Federated Learning by Distribution Shifts Aware Client Indexing ICCV 2025
Cooperative Pseudo Labeling for Unsupervised Federated Classification ICCV 2025
FedMeNF: Privacy-Preserving Federated Meta-Learning for Neural Fields ICCV 2025
LoRA-FAIR: Federated LoRA Fine-Tuning with Aggregation and Initialization Refinement ICCV 2025
Stealthy Backdoor Attack in Federated Learning via Adaptive Layer-wise Gradient Alignment ICCV 2025
Graph Consistency and Diversity Measurement for Federated Multi-View Clustering AAAI 2025
Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback JMLR 2025
PFLlib: A Beginner-Friendly and Comprehensive Personalized Federated Learning Library and Benchmark JMLR 2025
FedMIA: An Effective Membership Inference Attack Exploiting "All for One" Principle in Federated Learning CVPR 2025
Reputation-aware Revenue Allocation for Auction-based Federated Learning AAAI 2025
AFL: A Single-Round Analytic Approach for Federated Learning with Pre-trained Models CVPR 2025
Frequentist Guarantees of Distributed (Non)-Bayesian Inference JMLR 2025
Federated Source-Free Domain Adaptation for Classification: Weighted Cluster Aggregation for Unlabeled Data WACV 2025
Geminio: Language-Guided Gradient Inversion Attacks in Federated Learning ICCV 2025
A Simple Data Augmentation for Feature Distribution Skewed Federated Learning CVPR 2025
Personalized Mixture of Experts for Multi-Site Medical Image Segmentation WACV 2025
When Cars Meet Drones: Hyperbolic Federated Learning for Source-Free Domain Adaptation in Adverse Weather WACV 2025
FedBG: Proactively Mitigating Bias in Cross-Domain Graph Federated Learning Using Background Data IJCAI 2025
A Federated Framework for LLM-based Recommendation NAACL 2025
Federated Multi-view Graph Clustering with Incomplete Attribute Imputation IJCAI 2025
Heterogeneous Federated Learning with Scalable Server Mixture-of-Experts IJCAI 2025
Mind the Cost of Scaffold! Benign Clients May Even Become Accomplices of Backdoor Attack ICCV 2025
dFLMoE: Decentralized Federated Learning via Mixture of Experts for Medical Data Analysis CVPR 2025
FedDifRC: Unlocking the Potential of Text-to-Image Diffusion Models in Heterogeneous Federated Learning ICCV 2025
Population Normalization for Federated Learning CVPR 2025