federated learning

Federated Context-Aware Personalized Recommendation AAAI 2026 Federated Cross-Modal Style-Aware Prompt Generation (Student Abstract) AAAI 2026 Federated EndoViT: Pretraining Vision Transformers via Federated Learning on Endoscopic Image Collections MIDL 2026 Federated Graph-level Clustering Network with Attribute Inference AAAI 2026 Federated Incomplete Multi-View Clustering with Tensorized Low-Rank Constraint AAAI 2026 Federated Learning Playground AAAI 2026 Federated Linear Dueling Bandits AAAI 2026 Federated Model Synchronization for Diagnostic Redefinition through a Novel Selective Parameter Unlearning WACV 2026 Federated Vision-Language-Recommendation with Personalized Fusion AAAI 2026 FedGRPO: Privately Optimizing Foundation Models with Group-Relative Rewards from Domain Clients AAAI 2026 FedHarmony: Harmonizing Heterogeneous Label Correlations in Federated Multi-Label Learning CVPR 2026 FedLAGC: Towards High Performance System-Heterogeneous Federated Learning via Layer-Adaptive Submodel Extraction and Gradient Correction AAAI 2026 FedMental: Evaluating Federated Learning for Mental Health Detection from Social Media Data ACL 2026 FedMerge: Federated Model Merging for Personalization AAAI 2026 FedMOP: Achieving Enhanced Privacy and Performance in Federated Learning via Momentum Orthogonal Projection CVPR 2026 FedMPT: Federated Multi-Label Prompt Tuning of Vision-Language Models CVPR 2026 FedP²EFT: Federated Learning to Personalize PEFT for Multilingual LLMs AAAI 2026 FedPAGR: Federated Prototype Alignment via Geometric Refinement for Heterogeneous Architectures ACL 2026 FedPM: Federated Learning Using Second-order Optimization with Preconditioned Mixing of Local Parameters AAAI 2026 FedRAC: Rolling Submodel Allocation for Collaborative Fairness in Federated Learning CVPR 2026 FedRE: A Representation Entanglement Framework for Model-Heterogeneous Federated Learning CVPR 2026 FedReFT: Federated Representation Fine-Tuning with All-But-Me Aggregation EACL 2026 FedRG: Unleashing the Representation Geometry for Federated Learning with Noisy Clients CVPR 2026 FedRNC: Addressing Spatio-Temporal Label Misalignment in Federated Noisy Class-Incremental Learning AAAI 2026 FedSCAl: Leveraging Server and Client Alignment for Unsupervised Federated Source-Free Domain Adaptation WACV 2026