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» Propagation Algorithms for Variational Bayesian Learning
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ICML
2008
IEEE
14 years 8 months ago
Memory bounded inference in topic models
What type of algorithms and statistical techniques support learning from very large datasets over long stretches of time? We address this question through a memory bounded version...
Ryan Gomes, Max Welling, Pietro Perona
IJAR
2008
167views more  IJAR 2008»
13 years 7 months ago
Approximate algorithms for credal networks with binary variables
This paper presents a family of algorithms for approximate inference in credal networks (that is, models based on directed acyclic graphs and set-valued probabilities) that contai...
Jaime Shinsuke Ide, Fabio Gagliardi Cozman
PKDD
2009
Springer
175views Data Mining» more  PKDD 2009»
14 years 2 months ago
Latent Dirichlet Bayesian Co-Clustering
Co-clustering has emerged as an important technique for mining contingency data matrices. However, almost all existing coclustering algorithms are hard partitioning, assigning each...
Pu Wang, Carlotta Domeniconi, Kathryn B. Laskey
PRL
2008
118views more  PRL 2008»
13 years 7 months ago
Bayes Machines for binary classification
In this work we propose an approach to binary classification based on an extension of Bayes Point Machines. Particularly, we take into account the whole set of hypotheses that are...
Daniel Hernández-Lobato, José Miguel...
ICIP
2010
IEEE
13 years 5 months ago
Natural image matting for multiple wide-baseline views
In this paper we present a novel approach to estimate the alpha mattes of a foreground object captured by a widebaseline circular camera rig provided a single key frame trimap. Ba...
Muhammad Sarim, Adrian Hilton, Jean-Yves Guillemau...