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» Topologically-constrained latent variable models
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EMNLP
2010
13 years 7 months ago
Holistic Sentiment Analysis Across Languages: Multilingual Supervised Latent Dirichlet Allocation
In this paper, we develop multilingual supervised latent Dirichlet allocation (MLSLDA), a probabilistic generative model that allows insights gleaned from one language's data...
Jordan L. Boyd-Graber, Philip Resnik
KDD
2004
ACM
210views Data Mining» more  KDD 2004»
14 years 10 months ago
Web usage mining based on probabilistic latent semantic analysis
The primary goal of Web usage mining is the discovery of patterns in the navigational behavior of Web users. Standard approaches, such as clustering of user sessions and discoveri...
Xin Jin, Yanzan Zhou, Bamshad Mobasher
JMLR
2010
192views more  JMLR 2010»
13 years 4 months ago
Efficient Learning of Deep Boltzmann Machines
We present a new approximate inference algorithm for Deep Boltzmann Machines (DBM's), a generative model with many layers of hidden variables. The algorithm learns a separate...
Ruslan Salakhutdinov, Hugo Larochelle
KDD
2006
ACM
175views Data Mining» more  KDD 2006»
14 years 10 months ago
A mixture model for contextual text mining
Contextual text mining is concerned with extracting topical themes from a text collection with context information (e.g., time and location) and comparing/analyzing the variations...
Qiaozhu Mei, ChengXiang Zhai
ICML
2010
IEEE
13 years 11 months ago
High-Performance Semi-Supervised Learning using Discriminatively Constrained Generative Models
We develop a semi-supervised learning method that constrains the posterior distribution of latent variables under a generative model to satisfy a rich set of feature expectation c...
Gregory Druck, Andrew McCallum