Parallel Software for Training Large Scale Support Vector Machines on Multiprocessor Systems

Provided by: University of Missouri-St. Louis
Topic: Hardware
Format: PDF
Parallel software for solving the quadratic program arising in training support vector machines for classification problems is introduced. The software implements an iterative decomposition technique and exploits both the storage and the computing resources available on multiprocessor systems, by distributing the heaviest computational tasks of each decomposition iteration. Based on a wide range of recent theoretical advances, relevant decomposition issues, such as the quadratic sub-problem solution, the gradient updating, the working set selection, are systematically described and their careful combination to get an effective parallel tool is discussed.

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