byzantine robustness 1federated learning 1heterogeneous data 1robust aggregation 1truncated-quadratic loss 1
From the 1 of 2 linked papers with an AI index.
2 papers
cs.LG2026
Enhanced Byzantine-Robust Federated Learning Via Truncated-Quadratic Loss for Heterogeneous Data
Zhi-Yong Wang, Hao Nan Sheng, Werner Stefan +3
The paper proposes a new aggregation rule based on truncated‑quadratic loss to improve Byzantine‑robust federated learning under heterogeneous and non‑convex data, showing theoreti…
cs.LG2025
Communication-Efficient and Privacy-Adaptable Mechanism for Federated Learning
Chih Wei Ling, Chun Hei Michael Shiu, Youqi Wu +4
Training machine learning models on decentralized private data via federated learning (FL) poses two key challenges: communication efficiency and privacy protection. In this work,…