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UAI
2004
15 years 8 months ago
Bayesian Learning in Undirected Graphical Models: Approximate MCMC Algorithms
Bayesian learning in undirected graphical models--computing posterior distributions over parameters and predictive quantities-is exceptionally difficult. We conjecture that for ge...
Iain Murray, Zoubin Ghahramani
WWW
2009
ACM
16 years 7 months ago
Understanding user's query intent with wikipedia
Understanding the intent behind a user's query can help search engine to automatically route the query to some corresponding vertical search engines to obtain particularly re...
Jian Hu, Gang Wang, Frederick H. Lochovsky, Jian-T...
195
Voted
CVPR
2000
IEEE
16 years 8 months ago
Learning in Gibbsian Fields: How Accurate and How Fast Can It Be?
?Gibbsian fields or Markov random fields are widely used in Bayesian image analysis, but learning Gibbs models is computationally expensive. The computational complexity is pronoun...
Song Chun Zhu, Xiuwen Liu
ISI
2006
Springer
15 years 6 months ago
Analyzing Entities and Topics in News Articles Using Statistical Topic Models
Statistical language models can learn relationships between topics discussed in a document collection and persons, organizations and places mentioned in each document. We present a...
David Newman, Chaitanya Chemudugunta, Padhraic Smy...
ACL
2012
13 years 9 months ago
Fine Granular Aspect Analysis using Latent Structural Models
In this paper, we present a structural learning model for joint sentiment classification and aspect analysis of text at various levels of granularity. Our model aims to identify ...
Lei Fang, Minlie Huang