Learning as search optimization: approximate large margin methods for structured prediction

Abstract

Mappings to structured output spaces (strings, trees, partitions, etc.) are typically learned using extensions of classification algorithms to simple graphical structures (eg., linear chains) in which search and parameter estimation can be performed exactly. Unfortunately, in many complex problems, it is rare that exact search or parameter estimation is… (More)
DOI: 10.1145/1102351.1102373

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@inproceedings{Daum2005LearningAS, title={Learning as search optimization: approximate large margin methods for structured prediction}, author={Hal Daum{\'e} and Daniel Marcu}, booktitle={ICML}, year={2005} }