4 papers · 1 filter
A homogeneous second-order descent method for nonconvex optimization
Chuwen Zhang, Dongdong Ge, Chang He +4
In this paper, we introduce a Homogeneous Second-Order Descent Method (HSODM) using the homogenized quadratic approximation to the original function. The merit of homogenization is…
A Single-Loop Robust Policy Gradient Method for Robust Markov Decision Processes
Zhenwei Lin, Chenyu Xue, Qi Deng +1
Robust Markov Decision Processes (RMDPs) have recently been recognized as a valuable and promising approach to discovering a policy with creditable performance, particularly in the…
A Homogenization Approach for Gradient-Dominated Stochastic Optimization
Jiyuan Tan, Chenyu Xue, Chuwen Zhang +3
Gradient dominance property is a condition weaker than strong convexity, yet sufficiently ensures global convergence even in non-convex optimization. This property finds wide appli…
An Enhanced ADMM-based Interior Point Method for Linear and Conic Optimization
Qi Deng, Qing Feng, Wenzhi Gao +8
The ADMM-based interior point (ABIP, Lin et al. 2021) method is a hybrid algorithm that effectively combines interior point method (IPM) and first-order methods to achieve a perfor…