latent variable model

Inference with Multivariate Heavy-Tails in Linear Models NeurIPS 2010 Latent Variable Models for Predicting File Dependencies in Large-Scale Software Development NeurIPS 2010 Posterior Regularization for Structured Latent Variable Models JMLR 2010 Probabilistic latent variable models for distinguishing between cause and effect NeurIPS 2010 Reducing Label Complexity by Learning From Bags AISTATS 2010 Self-Paced Learning for Latent Variable Models NeurIPS 2010 Variational bounds for mixed-data factor analysis NeurIPS 2010 A Bayesian Analysis of Dynamics in Free Recall NeurIPS 2009 Clustering sequence sets for motif discovery NeurIPS 2009 Estimating image bases for visual image reconstruction from human brain activity NeurIPS 2009 Factor Modeling for Advertisement Targeting NeurIPS 2009 Learning GP-BayesFilters via Gaussian process latent variable models RSS 2009 Occlusive Components Analysis NeurIPS 2009 Posterior vs Parameter Sparsity in Latent Variable Models NeurIPS 2009 Probabilistic Relational PCA NeurIPS 2009 Evaluating probabilities under high-dimensional latent variable models NeurIPS 2008 Learning the Semantic Correlation: An Alternative Way to Gain from Unlabeled Text NeurIPS 2008 Logistic Normal Priors for Unsupervised Probabilistic Grammar Induction NeurIPS 2008 Mixed Membership Stochastic Blockmodels NeurIPS 2008 Building Blocks for Variational Bayesian Learning of Latent Variable Models JMLR 2007 Convex Relaxations of Latent Variable Training NeurIPS 2007 Discriminative Log-Linear Grammars with Latent Variables NeurIPS 2007 Expectation Maximization and Posterior Constraints NeurIPS 2007 Heterogeneous Component Analysis NeurIPS 2007 Modeling homophily and stochastic equivalence in symmetric relational data NeurIPS 2007