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JMLR
2010
143views more  JMLR 2010»
14 years 4 months ago
Incremental Sigmoid Belief Networks for Grammar Learning
We propose a class of Bayesian networks appropriate for structured prediction problems where the Bayesian network's model structure is a function of the predicted output stru...
James Henderson, Ivan Titov
ICASSP
2010
IEEE
14 years 9 months ago
Supervised topic model for automatic image annotation
This paper presents a new probabilistic model for the task of image annotation. Our model, which we call sLDA-bin, extends supervised Latent Dirichlet Allocation (sLDA) model to h...
Duangmanee Putthividhya, Hagai Thomas Attias, Srik...
ICA
2007
Springer
15 years 1 months ago
Conjugate Gamma Markov Random Fields for Modelling Nonstationary Sources
In modelling nonstationary sources, one possible strategy is to define a latent process of strictly positive variables to model variations in second order statistics of the underly...
Ali Taylan Cemgil, Onur Dikmen
ICML
2009
IEEE
15 years 10 months ago
MedLDA: maximum margin supervised topic models for regression and classification
Supervised topic models utilize document's side information for discovering predictive low dimensional representations of documents; and existing models apply likelihoodbased...
Jun Zhu, Amr Ahmed, Eric P. Xing
JMLR
2012
13 years 20 hour ago
Factorized Asymptotic Bayesian Inference for Mixture Modeling
This paper proposes a novel Bayesian approximation inference method for mixture modeling. Our key idea is to factorize marginal log-likelihood using a variational distribution ove...
Ryohei Fujimaki, Satoshi Morinaga