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Title:Solving Very Large Scale Linear SVM Using Multiple Processors
Author(s):Jindal, Prateek; Roth, Dan; Kale, Laxmikant V.
Subject(s):Support Vector Machines
Big Data Analytics
Charm++
Abstract:SVMs have been used for long for data classification. While solving very large problems, one may encounter hundreds of thousands of features and a large number of training vectors. A natural solution to solving problems with large datasets is to use multiple processors. In this report, we discuss the parallel implementation of Liblinear which is a very good sequential tool for using SVMs.
Issue Date:2013-12-04
Citation Info:Prateek Jindal, Dan Roth, L.V. Kale. Solving Very Large Scale Linear SVM Using Multiple Processors. Computer Science Research and Tech Reports. UIUC. 2013.
Genre:Technical Report
Type:Text
Language:English
URI:http://hdl.handle.net/2142/46407
Publication Status:unpublished
Peer Reviewed:not peer reviewed
Rights Information:2013 by Prateek Jindal
Date Available in IDEALS:2013-12-04


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