4 papers · 1 filter
An accelerated proximal bundle method for convex optimization
Feng-Yi Liao, Thomas Madden, Yang Zheng
The proximal bundle method (PBM) is a powerful and widely used approach for minimizing nonsmooth convex functions. However, for smooth objectives, its best-known convergence rate r…
Policy Optimization in Robust Control: Weak Convexity and Subgradient Methods
Yuto Watanabe, Feng-Yi Liao, Yang Zheng
Robust control seeks stabilizing policies that perform reliably under adversarial disturbances, with control as a classical formulation. It is known that polic…
A Proximal Descent Method for Minimizing Weakly Convex Optimization
Feng-Yi Liao, Yang Zheng
We study the problem of minimizing a -weakly convex and possibly nonsmooth function. Weak convexity provides a broad framework that subsumes convex, smooth, and many composite n…
A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles
Feng-Yi Liao, Yang Zheng
We propose a new bundle-based augmented Lagrangian framework for solving constrained convex problems. Unlike the classical (inexact) augmented Lagrangian method (ALM) that has a ne…