A unified algorithm for mixed \(l_{2,p}\)-minimizations and its application in feature selection
type: Item
instance of: scholarly article
title: A unified algorithm for mixed \(l_{2,p}\)-minimizations and its application in feature selection
zbMATH Open document ID: 1305.90339
author: Li-ping Wang
author: Yuanping Wang
author: Songcan Chen
published in: Computational Optimization and Applications
publication date: 2014-09-26T00:00:00Z
Mathematics Subject Classification ID: 90C26
zbMATH DE Number: 6348486
zbMATH Keywords: mixed matrix norm
zbMATH Keywords: non-Lipschitz continuous
zbMATH Keywords: unified algorithm
zbMATH Keywords: gradient projection
MaRDI profile type: Publication
full work available at URL: s10589-014-9648-x
OpenAlex ID: W2068320780
cites work: The Gradient Projection Method for Nonlinear Programming. Part I. Linear Constraints
cites work: Enhancing sparsity by reweighted \(\ell _{1}\) minimization
cites work: Lower Bound Theory of Nonzero Entries in Solutions of $\ell_2$-$\ell_p$ Minimization
cites work: Comparison of Discrimination Methods for the Classification of Tumors Using Gene Expression Data
DOI: 10.1007/S10589-014-9648-X
description: scientific article; zbMATH DE number 6348486