Towards ultrahigh dimensional feature selection for big data
In this paper, we present a new adaptive feature scaling scheme for ultrahigh-dimensional feature selection on Big Data, and then reformulate it as a convex semi-infinite programming (SIP) problem. To address the SIP, we propose an eficient feature generating paradigm. Different from traditional gra...
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Main Authors: | , , |
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Other Authors: | |
Format: | Article |
Language: | English |
Published: |
2014
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/105805 http://hdl.handle.net/10220/20902 http://www.jmlr.org/papers/v15/tan14a.html |
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Institution: | Nanyang Technological University |
Language: | English |