Unsupervised feature selection based on self-representation sparse regression and local similarity preserving

标题
Unsupervised feature selection based on self-representation sparse regression and local similarity preserving
作者
关键词
Unsupervised feature selection, Sparse reconstruction, Similarity preserving, <em class=EmphasisTypeItalic >L</em><sub>2,1/2</sub>-matrix norm
出版商
Springer Nature
发表日期
2017-12-18
DOI
10.1007/s13042-017-0760-y

向作者/读者发起求助以获取更多资源

Reprint

联系作者

Find Funding. Review Successful Grants.

Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.

Explore

Ask a Question. Answer a Question.

Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.

Get Started