Optimized cutting plane algorithm for support vector machines

  title={Optimized cutting plane algorithm for support vector machines},
  author={Vojtech Franc and S{\"o}ren Sonnenburg},
We have developed a new Linear Support Vector Machine (SVM) training algorithm called OCAS. Its computational effort scales linearly with the sample size. In an extensive empirical evaluation OCAS significantly outperforms current state of the art SVM solvers, like SVMlight, SVMperf and BMRM, achieving speedups of over 1,000 on some datasets over SVMlight and 20 over SVMperf, while obtaining the same precise Support Vector solution. OCAS even in the early optimization steps shows often faster… CONTINUE READING
Highly Influential
This paper has highly influenced 17 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS
Highly Cited
This paper has 144 citations. REVIEW CITATIONS


Publications citing this paper.
Showing 1-10 of 85 extracted citations

144 Citations

Citations per Year
Semantic Scholar estimates that this publication has 144 citations based on the available data.

See our FAQ for additional information.


Publications referenced by this paper.

Similar Papers

Loading similar papers…