3 papers
math.OC2025
OFF Newton-type Methods for Unconstrained Optimization with Inexact Derivatives
Hong Zhu
We study objective-function-free (OFF) Newton-type methods for smooth unconstrained optimization with inexact gradients and Hessians. We propose two methods for first- and second-o…
math.OC2024
An Inexact Proximal Newton Method for Nonconvex Composite Minimization
Hong Zhu
In this paper, we propose an inexact proximal Newton-type method for nonconvex composite problems. We establish the global convergence rate of the order in…
math.OC2024
A Stochastic Block-coordinate Proximal Newton Method for Nonconvex Composite Minimization
Hong Zhu, Xun Qian
This paper presents a stochastic block-coordinate proximal Newton method for minimizing the sum of a blockwise Lipschitz-continuously differentiable function and a separable nonsmo…