Federated Learning

ECC-SNN: Cost-Effective Edge-Cloud Collaboration for Spiking Neural Networks IJCAI 2025 EcoLoRA: Communication-Efficient Federated Fine-Tuning of Large Language Models EMNLP 2025 Efficient Federated Learning via Clients-to-Server Knowledge Distillation (Student Abstract) AAAI 2025 Efficient Multi-agent Offline Coordination via Diffusion-based Trajectory Stitching ICLR 2025 EFSkip: A New Error Feedback with Linear Speedup for Compressed Federated Learning with Arbitrary Data Heterogeneity AAAI 2025 EFTViT: Efficient Federated Training of Vision Transformers with Masked Images on Resource-Constrained Clients ICCV 2025 Emerging Safety Attack and Defense in Federated Instruction Tuning of Large Language Models ICLR 2025 Energy-based Backdoor Defense Against Federated Graph Learning ICLR 2025 Enhancing Clustered Federated Learning: Integration of Strategies and Improved Methodologies ICLR 2025 Enhancing Federated Domain Adaptation with Multi-Domain Prototype-Based Federated Fine-Tuning ICLR 2025 Enhancing Model Privacy in Federated Learning with Random Masking and Quantization EMNLP 2025 Enhancing Privacy in the Early Detection of Sexual Predators Through Federated Learning and Differential Privacy AAAI 2025 Enhancing the Performance of Global Model by Improving the Adaptability of Local Models in Federated Learning IJCAI 2025 Event-Driven Online Vertical Federated Learning ICLR 2025 Exploit Gradient Skewness to Circumvent Byzantine Defenses for Federated Learning AAAI 2025 Exploiting Label Skewness for Spiking Neural Networks in Federated Learning IJCAI 2025 Exploring Vacant Classes in Label-Skewed Federated Learning AAAI 2025 F^3OCUS - Federated Finetuning of Vision-Language Foundation Models with Optimal Client Layer Updating Strategy via Multi-objective Meta-Heuristics CVPR 2025 Fair Federated Survival Analysis AAAI 2025 FAST: A Lightweight Mechanism Unleashing Arbitrary Client Participation in Federated Learning IJCAI 2025 FCOM: A Federated Collaborative Online Monitoring Framework via Representation Learning AAAI 2025 FDPT: Federated Discrete Prompt Tuning for Black-Box Visual-Language Models ICCV 2025 Feasibility of Federated Learning from Client Databases with Different Brain Diseases and MRI Modalities WACV 2025 FedAA: A Reinforcement Learning Perspective on Adaptive Aggregation for Fair and Robust Federated Learning AAAI 2025 FedAPA: Server-side Gradient-Based Adaptive Personalized Aggregation for Federated Learning on Heterogeneous Data IJCAI 2025