Monte Carlo MCMC: Efficient Inference by Approximate Sampling

Sameer Singh, Michael Wick, Andrew McCallum


Anthology ID:
D12-1101
Volume:
Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
Month:
July
Year:
2012
Address:
Jeju Island, Korea
Editors:
Jun’ichi Tsujii, James Henderson, Marius Paşca
Venue:
EMNLP
SIGs:
SIGDAT | SIGNLL
Publisher:
Association for Computational Linguistics
Note:
Pages:
1104–1113
Language:
URL:
https://aclanthology.org/D12-1101
DOI:
Bibkey:
Cite (ACL):
Sameer Singh, Michael Wick, and Andrew McCallum. 2012. Monte Carlo MCMC: Efficient Inference by Approximate Sampling. In Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, pages 1104–1113, Jeju Island, Korea. Association for Computational Linguistics.
Cite (Informal):
Monte Carlo MCMC: Efficient Inference by Approximate Sampling (Singh et al., EMNLP 2012)
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PDF:
https://preview.aclanthology.org/nschneid-patch-2/D12-1101.pdf