The kernelized stochastic batch perceptron

Andrew Cotter*, Shai Shalev-Shwartz, Nathan Srebro

*Corresponding author for this work

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

7 Scopus citations

Abstract

We present a novel approach for training kernel Support Vector Machines, establish learning runtime guarantees for our method that are better then those of any other known kernelized SVM optimization approach, and show that our method works well in practice compared to existing alternatives.

Original languageAmerican English
Title of host publicationProceedings of the 29th International Conference on Machine Learning, ICML 2012
Pages943-950
Number of pages8
StatePublished - 2012
Event29th International Conference on Machine Learning, ICML 2012 - Edinburgh, United Kingdom
Duration: 26 Jun 20121 Jul 2012

Publication series

NameProceedings of the 29th International Conference on Machine Learning, ICML 2012
Volume1

Conference

Conference29th International Conference on Machine Learning, ICML 2012
Country/TerritoryUnited Kingdom
CityEdinburgh
Period26/06/121/07/12

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