Improvements on sequential minimal optimization algorithm for support vector machine based on semi-sparse algorithm

  • Xiaopeng Yang*
  • , Hu Guan
  • , Feilong Tang
  • , Ilsun You
  • , Minyi Guo
  • , Yao Shen
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Sequential Minimal Optimization (SMO) is one of simple but fast iterative algorithm for Support Vector Machine (SVM), while there is a large amount of vector multiplication in SMO, which is still expensive and time-consuming. In this paper, we propose our Semi-sparse algorithm to enhance the vector multiplication in the SMO algorithms for large-scale sparse matrices. In the worst scenario, the traditional sparse algorithm on SMO needs O(n1+n2) times of judgments and addressing on two sparse vectors which own m and n elements respectively, while Semi-sparse algorithm can nearly finish this multiplying process within O(n2). Our experimental results on two benchmarks show that the modified SVMTorch based on our Semi-sparse algorithm can perform significantly faster than SVMTorch based on the original sparse algorithm.

Original languageEnglish
Title of host publicationProceedings - 2011 5th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, IMIS 2011
Pages192-199
Number of pages8
DOIs
StatePublished - 2011
Externally publishedYes
Event2011 5th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, IMIS 2011 - Seoul, Korea, Republic of
Duration: 30 Jun 20112 Jul 2011

Publication series

NameProceedings - 2011 5th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, IMIS 2011

Conference

Conference2011 5th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, IMIS 2011
Country/TerritoryKorea, Republic of
CitySeoul
Period30/06/112/07/11

Keywords

  • SVM
  • Semi-sparse Algorithm
  • Sequential Minimal Optimization
  • Vector Multiplication

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