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ICML
2009
IEEE

Learning structural SVMs with latent variables

10 years 4 months ago
Learning structural SVMs with latent variables
We present a large-margin formulation and algorithm for structured output prediction that allows the use of latent variables. Our proposal covers a large range of application problems, with an optimization problem that can be solved efficiently using ConcaveConvex Programming. The generality and performance of the approach is demonstrated through three applications including motiffinding, noun-phrase coreference resolution, and optimizing precision at k in information retrieval.
Chun-Nam John Yu, Thorsten Joachims
Added 17 Nov 2009
Updated 17 Nov 2009
Type Conference
Year 2009
Where ICML
Authors Chun-Nam John Yu, Thorsten Joachims
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