A cyclic block coordinate descent method with generalized gradient projections
Numerical Analysis
2016-05-13 v1
Abstract
The aim of this paper is to present the convergence analysis of a very general class of gradient projection methods for smooth, constrained, possibly nonconvex, optimization. The key features of these methods are the Armijo linesearch along a suitable descent direction and the non Euclidean metric employed to compute the gradient projection. We develop a very general framework from the point of view of block--coordinate descent methods, which are useful when the constraints are separable.
Cite
@article{arxiv.1502.06737,
title = {A cyclic block coordinate descent method with generalized gradient projections},
author = {Silvia Bonettini and Marco Prato and Simone Rebegoldi},
journal= {arXiv preprint arXiv:1502.06737},
year = {2016}
}
Comments
arXiv admin note: substantial text overlap with arXiv:1406.6601