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Federated Learning

1355 directly classified papers

Papers per year

Papers

FedSPA: Generalizable Federated Graph Learning under Homophily Heterogeneity CVPR 2025
Class-Wise Federated Averaging for Efficient Personalization ICCV 2025
Mind the Gap: Confidence Discrepancy Can Guide Federated Semi-Supervised Learning Across Pseudo-Mismatch CVPR 2025
Federated Domain Generalization with Decision Insight Matrix IJCAI 2025
MultiSFL: Towards Accurate Split Federated Learning via Multi-Model Aggregation and Knowledge Replay AAAI 2025
MFL-Owner: Ownership Protection for Multi-modal Federated Learning via Orthogonal Transform Watermark AAAI 2025
Overcoming Heterogeneous Data in Federated Medical Vision-Language Pre-training: A Triple-Embedding Model Selector Approach AAAI 2025
Personalized Federated Learning for Spatio-Temporal Forecasting: A Dual Semantic Alignment-Based Contrastive Approach AAAI 2025
Federated Recommendation with Explicitly Encoding Item Bias AAAI 2025
Inconsistency-Based Federated Active Learning IJCAI 2025
FedCM: Client Clustering and Migration in Federated Learning via Gradient Path Similarity and Update Direction Deviation IJCAI 2025
Personalized Label Inference Attack in Federated Transfer Learning via Contrastive Meta Learning AAAI 2025
Attribute Inference Attacks for Federated Regression Tasks AAAI 2025
Mjölnir: Breaking the Shield of Perturbation-Protected Gradients via Adaptive Diffusion AAAI 2025
SADBA: Self-Adaptive Distributed Backdoor Attack Against Federated Learning AAAI 2025
Beyond Federated Prototype Learning: Learnable Semantic Anchors with Hyperspherical Contrast for Domain-Skewed Data AAAI 2025
Virtual Nodes Can Help: Tackling Distribution Shifts in Federated Graph Learning AAAI 2025
Optimizing Personalized Federated Learning Through Adaptive Layer-Wise Learning IJCAI 2025
Incongruent Multimodal Federated Learning for Medical Vision and Language-based Multi-label Disease Detection AAAI 2025
HaCore: Efficient Coreset Construction with Locality Sensitive Hashing for Vertical Federated Learning AAAI 2025
DCHM: Dynamic Collaboration of Heterogeneous Models Through Isomerism Learning in a Blockchain-Powered Federated Learning Framework AAAI 2025
Finite-Time Analysis of Heterogeneous Federated Temporal Difference Learning IJCAI 2025
An Efficient and Accurate Dynamic Sparse Training Framework Based on Parameter-Freezing AAAI 2025
Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization IJCAI 2025
ConFREE: Conflict-free Client Update Aggregation for Personalized Federated Learning AAAI 2025