Proximal quasi-Newton methods for regularized convex optimization with linear and accelerated sublinear convergence rates
Sign Up to like & getrecommendations! Published in 2018 at "Computational Optimization and Applications"
DOI: 10.1007/s10589-017-9964-z
Abstract: A general, inexact, efficient proximal quasi-Newton algorithm for composite optimization problems has been proposed by Scheinberg and Tang (Math Program 160:495–529, 2016) and a sublinear global convergence rate has been established. In this paper, we… read more here.
Keywords: newton algorithm; proximal quasi; quasi newton; optimization ... See more keywords
Stochastic proximal quasi-Newton methods for non-convex composite optimization
Sign Up to like & getrecommendations! Published in 2019 at "Optimization Methods and Software"
DOI: 10.1080/10556788.2018.1471141
Abstract: ABSTRACT In this paper, we propose a generic algorithmic framework for stochastic proximal quasi-Newton (SPQN) methods to solve non-convex composite optimization problems. Stochastic second-order information is explored to construct proximal subproblem. Under mild conditions we… read more here.
Keywords: stochastic proximal; proximal quasi; quasi newton; optimization ... See more keywords