Multi-class classification with maximum margin multiple kernel

Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh

Research output: Contribution to conferencePaper

Abstract

We present a new algorithm for multi-class classification with multiple kernels. Our algorithm is based on a natural notion of the multi-class margin of a kernel. We show that larger values of this quantity guarantee the existence of an accurate multi-class predictor and also define a family of multiple kernel algorithms based on the maximization of the multi-class margin of a kernel (M3K). We present an extensive theoretical analysis in support of our algorithm, including novel multi-class Rademacher complexity margin bounds. Finally, we also report the results of a series of experiments with several data sets, including comparisons where we improve upon the performance of state-of-the-art algorithms both in binary and multi-class classification with multiple kernels.

Original languageEnglish (US)
Pages1083-1091
Number of pages9
StatePublished - 2013
Event30th International Conference on Machine Learning, ICML 2013 - Atlanta, GA, United States
Duration: Jun 16 2013Jun 21 2013

Other

Other30th International Conference on Machine Learning, ICML 2013
CountryUnited States
CityAtlanta, GA
Period6/16/136/21/13

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Sociology and Political Science

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    Cortes, C., Mohri, M., & Rostamizadeh, A. (2013). Multi-class classification with maximum margin multiple kernel. 1083-1091. Paper presented at 30th International Conference on Machine Learning, ICML 2013, Atlanta, GA, United States.