5 citations · 5 across the 3 of their papers we have counts for
3 papers
cs.LG2026
Accelerating Byzantine-Robust Distributed Learning with Compressed Communication via Double Momentum and Variance Reduction
Yanghao Li, Changxin Liu, Yuhao Yi
In collaborative and distributed learning, Byzantine robustness reflects a major facet of optimization algorithms. Such distributed algorithms are often accompanied by transmitting…
cs.LG2024
Byzantine-Robust and Communication-Efficient Distributed Learning via Compressed Momentum Filtering
Changxin Liu, Yanghao Li, Yuhao Yi +1
Distributed learning has become the standard approach for training large-scale machine learning models across private data silos. While distributed learning enhances privacy preser…
cs.LG2023★ 5 cited
Near-Optimal Resilient Aggregation Rules for Distributed Learning Using 1-Center and 1-Mean Clustering with Outliers
Yuhao Yi, Ronghui You, Hong Liu +3
Byzantine machine learning has garnered considerable attention in light of the unpredictable faults that can occur in large-scale distributed learning systems. The key to secure re…