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概率建模与推断(4)—— 概率图模型(未完成草稿)

1 minute read

Published:

作者:Michael Gutmann(迈克尔·古特曼)
译者:郭尚敏(Shangmin Guo),shawnguo.cn@gmail.com
版权声明:本系列博客翻译自作者 迈克尔·古特曼 在爱丁堡大学(The University of Edinburgh)2019春季学期“概率建模与推断”(Probabilistic Modelling and Reasoning,INFR11134)课程的授课课件。译者已经取得原作者的翻译授权。
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概率建模与推断(3)—— 有向图与独立性假设

1 minute read

Published:

作者:Michael Gutmann(迈克尔·古特曼)
译者:郭尚敏(Shangmin Guo),shawnguo.cn@gmail.com
版权声明:本系列博客翻译自作者 迈克尔·古特曼 在爱丁堡大学(The University of Edinburgh)2019春季学期“概率建模与推断”(Probabilistic Modelling and Reasoning,INFR11134)课程的授课课件。译者已经取得原作者的翻译授权。
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概率建模与推断(2)—— 高效模型表示的基本假设

less than 1 minute read

Published:

作者:Michael Gutmann(迈克尔·古特曼)
译者:郭尚敏(Shangmin Guo),shawnguo.cn@gmail.com
版权声明:本系列博客翻译自作者 迈克尔·古特曼 在爱丁堡大学(The University of Edinburgh)2019春季学期“概率建模与推断”(Probabilistic Modelling and Reasoning,INFR11134)课程的授课课件。译者已经取得原作者的翻译授权。
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概率建模与推断(1)——引言

less than 1 minute read

Published:

作者:Michael Gutmann(迈克尔·古特曼)
译者:郭尚敏(Shangmin Guo),shawnguo.cn@gmail.com
版权声明:本系列博客翻译自作者 迈克尔·古特曼 在爱丁堡大学(The University of Edinburgh)2019春季学期“概率建模与推断”(Probabilistic Modelling and Reasoning,INFR11134)课程的授课课件。译者已经取得原作者的翻译授权。
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publications

Which is the Effective Way for Gaokao: Information Retrieval or Neural Networks?

Published in EACL-2017, 2017

This paper discusses different methods for taking the challenges of Gaokao history multi-choice questions. Read more

Recommended citation: Guo, Shangmin, Xiangrong Zeng, Shizhu He, Kang Liu, and Jun Zhao. "Which is the Effective Way for Gaokao: Information Retrieval or Neural Networks?." In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers, pp. 111-120. 2017. https://www.aclweb.org/anthology/E17-1011