Learning and Inference over Constrained Output

Punyakanok, Vasin; Roth, Dan; Yih, Wen-tau; Zimak, Dav

Learning and Inference over Constrained Output

Vasin Punyakanok, Dan Roth, Wen-tau Yih, Dav Zimak

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Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence. Pages 1124-1128.

Abstract

We study learning structured output in a discriminative framework where values of the output variables are estimated by local classifiers. In this framework, complex dependencies among the output variables are captured by constraints and dictate which global labels can be inferred. We compare two strategies, learning independent classifiers and inference based training, by observing their behaviors in different conditions. Experiments and theoretical justification lead to the conclusion that using inference based learning is superior when the local classifiers are difficult to learn but may require many examples before any discernible difference can be observed.

Vasin Punyakanok, Dan Roth, Wen-tau Yih, and Dav Zimak. 2005. Learning and Inference over Constrained Output. In Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, IJCAI-05. IJCAI, 1124–1128. https://ijcai.org/proceedings/2005/180

@inproceedings{ijcai2005p180,
  title     = {Learning and Inference over Constrained Output},
  author    = {Punyakanok, Vasin and Roth, Dan and Yih, Wen-tau and Zimak, Dav},
  booktitle = {Proceedings of the Nineteenth International Joint Conference on
               Artificial Intelligence, {IJCAI-05}},
  publisher = {International Joint Conferences on Artificial Intelligence},
  pages     = {1124--1128},
  year      = {2005},
  url       = {https://ijcai.org/proceedings/2005/180},
}

TY  - CPAPER
TI  - Learning and Inference over Constrained Output
AU  - Punyakanok, Vasin
AU  - Roth, Dan
AU  - Yih, Wen-tau
AU  - Zimak, Dav
T2  - Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, IJCAI-05
PB  - International Joint Conferences on Artificial Intelligence
PY  - 2005
SP  - 1124
EP  - 1128
UR  - https://ijcai.org/proceedings/2005/180
ER  -