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» Unsupervised estimation for noisy-channel models
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NIPS
2004
14 years 11 months ago
Parametric Embedding for Class Visualization
In this paper, we propose a new method, Parametric Embedding (PE), for visualizing the posteriors estimated over a mixture model. PE simultaneously embeds both objects and their c...
Tomoharu Iwata, Kazumi Saito, Naonori Ueda, Sean S...
ACL
2008
14 years 11 months ago
Bayesian Learning of Non-Compositional Phrases with Synchronous Parsing
We combine the strengths of Bayesian modeling and synchronous grammar in unsupervised learning of basic translation phrase pairs. The structured space of a synchronous grammar is ...
Hao Zhang, Chris Quirk, Robert C. Moore, Daniel Gi...
ACL
2009
14 years 7 months ago
Semi-supervised Learning of Dependency Parsers using Generalized Expectation Criteria
In this paper, we propose a novel method for semi-supervised learning of nonprojective log-linear dependency parsers using directly expressed linguistic prior knowledge (e.g. a no...
Gregory Druck, Gideon S. Mann, Andrew McCallum
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SIGIR
2004
ACM
15 years 3 months ago
Dependence language model for information retrieval
This paper presents a new dependence language modeling approach to information retrieval. The approach extends the basic language modeling approach based on unigram by relaxing th...
Jianfeng Gao, Jian-Yun Nie, Guangyuan Wu, Guihong ...
NIPS
2004
14 years 11 months ago
Hierarchical Distributed Representations for Statistical Language Modeling
Statistical language models estimate the probability of a word occurring in a given context. The most common language models rely on a discrete enumeration of predictive contexts ...
John Blitzer, Kilian Q. Weinberger, Lawrence K. Sa...