arXiv · 1811.11378
A Doubly Accelerated Inexact Proximal Point Method for Nonconvex Composite Optimization Problems
Abstract
This paper describes and establishes the iteration-complexity of a doubly accelerated inexact proximal point (D-AIPP) method for solving the nonconvex composite minimization problem whose objective function is of the form $f+h$ where $f$ is a (possibly nonconvex) differentiable function whose gradient is Lipschitz continuous and $h$ is a closed convex function with bounded domain. D-AIPP performs two types of iterations, namely, inner and outer ones. Its outer iterations correspond to the ones of the accelerated inexact proximal point scheme. Its inner iterations are the ones performed by an accelerated composite gradient method for inexactly solving the convex proximal subproblems generated during the outer iterations. Thus, D-AIPP employs both inner and outer accelerations.
Explore related subjects
Keep this discovery
Jiaming Liang, Renato D. C. Monteiro. 2018-11-28. A Doubly Accelerated Inexact Proximal Point Method for Nonconvex Composite Optimization Problems. https://arxiv.org/abs/1811.11378
Cite the original work for its findings. Save a collection to share your selection of sources.