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» Variational Inference for Adaptor Grammars
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NAACL
2010
13 years 8 months ago
Variational Inference for Adaptor Grammars
Adaptor grammars extend probabilistic context-free grammars to define prior distributions over trees with "rich get richer" dynamics. Inference for adaptor grammars seek...
Shay B. Cohen, David M. Blei, Noah A. Smith
ACL
2010
13 years 9 months ago
PCFGs, Topic Models, Adaptor Grammars and Learning Topical Collocations and the Structure of Proper Names
This paper establishes a connection between two apparently very different kinds of probabilistic models. Latent Dirichlet Allocation (LDA) models are used as "topic models&qu...
Mark Johnson
COLING
2010
13 years 5 months ago
Unsupervised phonemic Chinese word segmentation using Adaptor Grammars
Adaptor grammars are a framework for expressing and performing inference over a variety of non-parametric linguistic models. These models currently provide state-of-the-art perfor...
Mark Johnson, Katherine Demuth
ACL
2009
13 years 8 months ago
Variational Inference for Grammar Induction with Prior Knowledge
Variational EM has become a popular technique in probabilistic NLP with hidden variables. Commonly, for computational tractability, we make strong independence assumptions, such a...
Shay B. Cohen, Noah A. Smith
COLING
2010
13 years 5 months ago
Benchmarking for syntax-based sentential inference
We propose a methodology for investigating how well NLP systems handle meaning preserving syntactic variations. We start by presenting a method for the semi automated creation of ...
Paul Bédaride, Claire Gardent