Latent energy preserving embedding for unsupervised feature selection-Reference-Cited by-同舟云学术

Latent energy preserving embedding for unsupervised feature selection

Published:2022-12 Issue: Volume:132 Page:103794
ISSN:1051-2004
Container-title:Digital Signal Processing
language:en
Short-container-title:Digital Signal Processing

Author:

Song Zihao,Song Peng^ORCID

Funder

Southeast University

Fundamental Research Funds for the Central Universities

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Signal Processing,Artificial Intelligence,Applied Mathematics,Computer Vision and Pattern Recognition,Statistics, Probability and Uncertainty,Computational Theory and Mathematics

Reference63 articles.

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2. Robust unsupervised feature selection by nonnegative sparse subspace learning;Zheng;Neurocomputing,2019

3. Unsupervised discriminative projection for feature selection;Wang;IEEE Trans. Knowl. Data Eng.,2020

4. ℓ2,1 regularized correntropy for robust feature selection;He,2012

5. Supervised feature selection with orthogonal regression and feature weighting;Wu;IEEE Trans. Neural Netw. Learn. Syst.,2020

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