Title
Self-paced Learning for K-means Clustering Algorithm
Abstract
•Propose a novel clustering algorithm by adding the self-paced regularization factor.•Improve the problem of non-convex optimization is easy to fall into local optimal solution.•A linear self-paced regularization factor is used to distinguish between noise and normal samples.
Year
DOI
Venue
2020
10.1016/j.patrec.2018.08.028
Pattern Recognition Letters
Keywords
DocType
Volume
41A05,41A10,65D05,65D17
Journal
132
ISSN
Citations 
PageRank 
0167-8655
3
0.38
References 
Authors
25
5
Name
Order
Citations
PageRank
Yu Hao124817.42
Guoqiu Wen2424.77
Jiangzhang Gan3442.60
Wei Zheng420832.78
Cong Lei51025.56