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JMLR
2010
129views more  JMLR 2010»
13 years 2 months ago
Expectation Truncation and the Benefits of Preselection In Training Generative Models
We show how a preselection of hidden variables can be used to efficiently train generative models with binary hidden variables. The approach is based on Expectation Maximization (...
Jörg Lücke, Julian Eggert
EMNLP
2010
13 years 5 months ago
A Fast Fertility Hidden Markov Model for Word Alignment Using MCMC
A word in one language can be translated to zero, one, or several words in other languages. Using word fertility features has been shown to be useful in building word alignment mo...
Shaojun Zhao, Daniel Gildea
LOCA
2007
Springer
14 years 1 months ago
SocialMotion: Measuring the Hidden Social Life of a Building
In this paper we present an approach to analyzing the social behaviors that occur in a typical office space. We describe a system consisting of over 200 motion sensors connected ...
Christopher Richard Wren, Yuri A. Ivanov, Ishwinde...
ICMCS
2006
IEEE
344views Multimedia» more  ICMCS 2006»
14 years 1 months ago
Pattern Mining in Visual Concept Streams
Pattern mining algorithms are often much easier applied than quantitatively assessed. In this paper we address the pattern evaluation problem by looking at both the capability of ...
Lexing Xie, Shih-Fu Chang
ICIP
2007
IEEE
14 years 9 months ago
Image Denoising with Nonparametric Hidden Markov Trees
We develop a hierarchical, nonparametric statistical model for wavelet representations of natural images. Extending previous work on Gaussian scale mixtures, wavelet coefficients ...
Jyri J. Kivinen, Erik B. Sudderth, Michael I. Jord...