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ICML
2010
IEEE
14 years 11 months ago
Conditional Topic Random Fields
Generative topic models such as LDA are limited by their inability to utilize nontrivial input features to enhance their performance, and many topic models assume that topic assig...
Jun Zhu, Eric P. Xing
IJAR
2010
152views more  IJAR 2010»
14 years 8 months ago
Structural-EM for learning PDG models from incomplete data
Probabilistic Decision Graphs (PDGs) are a class of graphical models that can naturally encode some context specific independencies that cannot always be efficiently captured by...
Jens D. Nielsen, Rafael Rumí, Antonio Salme...
PAMI
2008
119views more  PAMI 2008»
14 years 9 months ago
Triplet Markov Fields for the Classification of Complex Structure Data
We address the issue of classifying complex data. We focus on three main sources of complexity, namely, the high dimensionality of the observed data, the dependencies between these...
Juliette Blanchet, Florence Forbes
NIPS
2008
14 years 11 months ago
Structure Learning in Human Sequential Decision-Making
We use graphical models and structure learning to explore how people learn policies in sequential decision making tasks. Studies of sequential decision-making in humans frequently...
Daniel Acuña, Paul R. Schrater
ACL
2010
14 years 7 months ago
Automatic Generation of Story Highlights
In this paper we present a joint content selection and compression model for single-document summarization. The model operates over a phrase-based representation of the source doc...
Kristian Woodsend, Mirella Lapata