Unsupervised feature selection by non-convex regularized self-representation-Reference-Cited by-同舟云学术

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Unsupervised feature selection by non-convex regularized self-representation

Published:2021-07 Issue: Volume:173 Page:114643
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Miao Jianyu,Ping Yuan,Chen Zhensong,Jin Xiao-Bo,Li Peijia,Niu Lingfeng

Funder

Science and Technology Innovation Talents in Universities of Henan Province

Education Department of Henan Province

Henan Province Foundation for University Key Teacher

Henan University of Technology

Science and Technology Department of Henan Province

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference52 articles.

1. Variable global feature selection scheme for automatic classification of text documents;Agnihotri;Expert Systems with Applications,2017

2. A feature selection based on perturbation theory;Anaraki;Expert Systems with Applications,2019

3. Argyriou, A., Evgeniou, T., & Pontil, M. (2007). Multi-task feature learning. In Advances in neural information processing systems (pp. 41–48).

4. A fast branch-and-bound algorithm for u-curve feature selection;Atashpaz-Gargari;Pattern Recognition,2018

5. Feature selection using joint mutual information maximisation;Bennasar;Expert Systems with Applications,2015

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