IEEE - Institute of Electrical and Electronics Engineers, Inc. - Sparse least squares support vector machine with L 0 -norm in primal space

2015 IEEE International Conference on Information and Automation (ICIA)

Author(s): Qi Li ; Xiaohang Li ; Wei Ba
Publisher: IEEE - Institute of Electrical and Electronics Engineers, Inc.
Publication Date: 1 August 2015
Conference Location: Lijiang, China
Conference Date: 8 August 2015
Page(s): 2,778 - 2,783
ISBN (Electronic): 978-1-4673-9104-7
ISBN (USB): 978-1-4673-9103-0
DOI: 10.1109/ICInfA.2015.7279758
Regular:

Least squares support vector machine (LS-SVM) has been successfully applied in many classification and regression tasks. The main drawback of the LS-SVM algorithm is the lack of sparseness.... View More

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