4 papers · 1 filter
Local Guidance, Global Impact: Gaussian-Reshaped Trust Region Unlocks Behavior Transitions
Bingxu Liu, Jiashun Liu, Johan Obando-Ceron +5
While Proximal Policy Optimization (PPO) demonstrates strong performance in stationary settings, we show that its standard optimization paradigm struggles in continual and non-stat…
Rethinking Bregman Divergences in Kronecker-Factored Optimizers
Bing Liu, Wenjie Zhou, Chengcheng Zhao
Shampoo-style optimizers approximate gradient covariance matrices using Kronecker-factored structures. Recent work~\cite{lin2026understanding} showed that such approximations can b…
Row-Stochastic Matrices Can Provably Outperform Doubly Stochastic Matrices in Decentralized Learning
Bing Liu, Boao Kong, Limin Lu +2
Decentralized learning often involves a weighted global loss with heterogeneous node weights . We revisit two natural strategies for incorporating these weights: (i) embedding t…
ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning
Bing Liu, Chengcheng Zhao, Li Chai +2
Jointly addressing Byzantine attacks and privacy leakage in distributed machine learning (DML) has become an important issue. A common strategy involves integrating Byzantine-resil…