@inproceedings{singh-etal-2012-monte,
title = "{M}onte {C}arlo {MCMC}: Efficient Inference by Approximate Sampling",
author = "Singh, Sameer and
Wick, Michael and
McCallum, Andrew",
editor = "Tsujii, Jun{'}ichi and
Henderson, James and
Pa{\c{s}}ca, Marius",
booktitle = "Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning",
month = jul,
year = "2012",
address = "Jeju Island, Korea",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D12-1101",
pages = "1104--1113",
}
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%0 Conference Proceedings
%T Monte Carlo MCMC: Efficient Inference by Approximate Sampling
%A Singh, Sameer
%A Wick, Michael
%A McCallum, Andrew
%Y Tsujii, Jun’ichi
%Y Henderson, James
%Y Paşca, Marius
%S Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
%D 2012
%8 July
%I Association for Computational Linguistics
%C Jeju Island, Korea
%F singh-etal-2012-monte
%U https://aclanthology.org/D12-1101
%P 1104-1113
Markdown (Informal)
[Monte Carlo MCMC: Efficient Inference by Approximate Sampling](https://aclanthology.org/D12-1101) (Singh et al., EMNLP 2012)
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.