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Solving Very Large Scale Linear SVM Using Multiple Processors

Year: 2013

Type: report

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.

Source: Illinois Digital Environment for Access to Learning and Scholarship (University of Illinois at Urbana-Champaign)

Authors: Prateek Jindal, Dan Roth, Laxmikant V. Kalé

Language: English

Topic: Parallel Computing and Optimization Techniques

Subfield: Hardware and Architecture

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W2591509989

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