NDLI: Efficient Algorithms for Selecting Features with Arbitrary Group Constraints via Group Lasso

Content Provider	IEEE Xplore Digital Library
Author	Deguang Kong Ding, C.
Copyright Year	2013
Description	Author affiliation: Dept. of Comp. Sci & Eng., Univ. of Texas at Arlington, Arlington, TX, USA (Deguang Kong; Ding, C.)
Abstract	Feature structure information plays an important role for regression and classification tasks. We consider a more generic problem: group lasso problem, where structures over feature space can be represented as a combination of features in a group. These groups can be either overlapped or non-overlapped, which are specified in different structures, e.g., structures over a line, a tree, a graph or even a forest. We propose a new approach to solve this generic group lasso problem, where certain features are selected in a group, and an arbitrary family of subset is allowed. We employ accelerated proximal gradient method to solve this problem, where a key step is solve the associated proximal operator. We propose a fast method to compute the proximal operator, where its convergence is rigorously proved. Experimental results on different structures (e.g., group, tree, graph structures) demonstrate the efficiency and effectiveness of the proposed algorithm.
Sponsorship	Toshiba
Starting Page	379
Ending Page	388
File Size	314059
Page Count	10
File Format	PDF
ISBN	9780769551081
ISSN	15504786
DOI	10.1109/ICDM.2013.168
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-12-07
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Vegetation Gradient methods Convergence Acceleration Input variables Standards Indexes exclusive lasso feature selection feature group constraint lasso group lasso
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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