@inproceedings{68e5085c36f0439e809eec7a540563a4,
title = "A improve direct path seeking algorithm for L 1/2 regularization, with application to biological feature selection",
abstract = "The special importance of L1/2 regularization has been recognized in recent studies on sparsity problems, particularly, on feature selection. The L1/2 regularization is nonconvex optimization problem, it is difficult in general to has a efficient algorithm to solutions. The direct path seeking method can produce solutions that closely approximate those for any convex loss function and nonconvex constraints. The improve path seeking methods provide us an effect way to solve the problem of L1/2 regularization with nonconvex penalty. In this paper, we investigate a improve direct path seeking algorithm to solve the L1/2 regularization. This method adopts initial ordinary regression coefficients as warm start for first step increment, it is significantly faster than ordinary path seeking algorithm. We demonstrate its performance of feature selection on several simulated and real data sets.",
keywords = "Direct path seeking algorithm, Feature selection, L1/2 regularization",
author = "Cheng Liu and Yong Liang and Luan, \{Xin Ze\} and Leung, \{Kwong Sak\} and Chan, \{Tak Ming\} and Xu, \{Zong Ben\} and Hai Zhang",
year = "2012",
doi = "10.1109/iCBEB.2012.28",
language = "英语",
isbn = "9780769547060",
series = "Proceedings - 2012 International Conference on Biomedical Engineering and Biotechnology, iCBEB 2012",
pages = "8--11",
booktitle = "Proceedings - 2012 International Conference on Biomedical Engineering and Biotechnology, iCBEB 2012",
note = "2012 International Conference on Biomedical Engineering and Biotechnology, iCBEB 2012 ; Conference date: 28-05-2012 Through 30-05-2012",
}