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» Propagation Algorithms for Variational Bayesian Learning
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AI
2010
Springer
14 years 10 months ago
Understanding the scalability of Bayesian network inference using clique tree growth curves
Bayesian networks (BNs) are used to represent and ef ciently compute with multi-variate probability distributions in a wide range of disciplines. One of the main approaches to per...
Ole J. Mengshoel
CVPR
2007
IEEE
15 years 11 months ago
Variational Bayes Based Approach to Robust Subspace Learning
This paper presents a new algorithm for the problem of robust subspace learning (RSL), i.e., the estimation of linear subspace parameters from a set of data points in the presence...
Takayuki Okatani, Koichiro Deguchi
WWW
2009
ACM
15 years 10 months ago
Matchbox: large scale online bayesian recommendations
We present a probabilistic model for generating personalised recommendations of items to users of a web service. The Matchbox system makes use of content information in the form o...
David H. Stern, Ralf Herbrich, Thore Graepel
NIPS
2003
14 years 11 months ago
Approximate Expectation Maximization
We discuss the integration of the expectation-maximization (EM) algorithm for maximum likelihood learning of Bayesian networks with belief propagation algorithms for approximate i...
Tom Heskes, Onno Zoeter, Wim Wiegerinck
EMNLP
2010
14 years 7 months ago
Turbo Parsers: Dependency Parsing by Approximate Variational Inference
We present a unified view of two state-of-theart non-projective dependency parsers, both approximate: the loopy belief propagation parser of Smith and Eisner (2008) and the relaxe...
André F. T. Martins, Noah A. Smith, Eric P....