Learning nonlinear dynamic models

John Langford, Ruslan Salakhutdinov, Tong Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We present a novel approach for learning nonlinear dynamic models, which leads to a new set of tools capable of solving problems that are otherwise difficult. We provide theory showing this new approach is consistent for models with long range structure, and apply the approach to motion capture and high-dimensional video data, yielding results superior to standard alternatives.

Original languageEnglish (US)
Title of host publicationProceedings of the 26th International Conference On Machine Learning, ICML 2009
Pages593-600
Number of pages8
StatePublished - 2009
Externally publishedYes
Event26th International Conference On Machine Learning, ICML 2009 - Montreal, QC, Canada
Duration: Jun 14 2009Jun 18 2009

Publication series

NameProceedings of the 26th International Conference On Machine Learning, ICML 2009

Conference

Conference26th International Conference On Machine Learning, ICML 2009
Country/TerritoryCanada
CityMontreal, QC
Period6/14/096/18/09

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Software

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