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CACM
2011
120views more  CACM 2011»
12 years 11 months ago
The sequence memoizer
We propose an unbounded-depth, hierarchical, Bayesian nonparametric model for discrete sequence data. This model can be estimated from a single training sequence, yet shares stati...
Frank Wood, Jan Gasthaus, Cédric Archambeau...
TASLP
2010
97views more  TASLP 2010»
12 years 11 months ago
Hierarchical Bayesian Language Models for Conversational Speech Recognition
Traditional n-gram language models are widely used in state-of-the-art large vocabulary speech recognition systems. This simple model suffers from some limitations, such as overfi...
Songfang Huang, Steve Renals
ACL
2011
12 years 8 months ago
A Bayesian Model for Unsupervised Semantic Parsing
We propose a non-parametric Bayesian model for unsupervised semantic parsing. Following Poon and Domingos (2009), we consider a semantic parsing setting where the goal is to (1) d...
Ivan Titov, Alexandre Klementiev
EMNLP
2010
13 years 2 months ago
Unsupervised Induction of Tree Substitution Grammars for Dependency Parsing
Inducing a grammar directly from text is one of the oldest and most challenging tasks in Computational Linguistics. Significant progress has been made for inducing dependency gram...
Phil Blunsom, Trevor Cohn
KDD
2008
ACM
257views Data Mining» more  KDD 2008»
14 years 5 months ago
Knowledge discovery of semantic relationships between words using nonparametric bayesian graph model
We developed a model based on nonparametric Bayesian modeling for automatic discovery of semantic relationships between words taken from a corpus. It is aimed at discovering seman...
Issei Sato, Minoru Yoshida, Hiroshi Nakagawa