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cs.LG2025
POLAR: Policy-based Layerwise Reinforcement Learning Method for Stealthy Backdoor Attacks in Federated Learning
Kuai Yu, Xiaoyu Wu, Peishen Yan +6
Federated Learning (FL) enables decentralized model training across multiple clients without exposing local data, but its distributed feature makes it vulnerable to backdoor attack…
cs.LG2025
THOR: A Generic Energy Estimation Approach for On-Device Training
Jiaru Zhang, Zesong Wang, Hao Wang +8
Battery-powered mobile devices (e.g., smartphones, AR/VR glasses, and various IoT devices) are increasingly being used for AI training due to their growing computational power and…
cs.DC2025
FedCod: An Efficient Communication Protocol for Cross-Silo Federated Learning with Coding
Peishen Yan, Jun Li, Hao Wang +4
Federated Learning (FL) is an innovative distributed machine learning paradigm that enables multiple parties to collaboratively train a model without sharing their raw data, thereb…