Probabilistic Modeling

A Method of Moments for Mixture Models and Hidden Markov Models COLT 2012 A P300 BCI for the Masses: Prior Information Enables Instant Unsupervised Spelling NeurIPS 2012 Approximate Message Passing with Consistent Parameter Estimation and Applications to Sparse Learning NeurIPS 2012 A Spectral Algorithm for Latent Dirichlet Allocation NeurIPS 2012 Assessing Blinding in Clinical Trials NeurIPS 2012 A Stick-Breaking Likelihood for Categorical Data Analysis with Latent Gaussian Models AISTATS 2012 Augment-and-Conquer Negative Binomial Processes NeurIPS 2012 Bayesian estimation of discrete entropy with mixtures of stick-breaking priors NeurIPS 2012 Bayesian nonparametric models for bipartite graphs NeurIPS 2012 Bayesian nonparametric models for ranked data NeurIPS 2012 Bayesian Probabilistic Co-Subspace Addition NeurIPS 2012 Bayesian regularization of non-homogeneous dynamic Bayesian networks by globally coupling interaction parameters AISTATS 2012 Bayesian Warped Gaussian Processes NeurIPS 2012 Beta-Negative Binomial Process and Poisson Factor Analysis AISTATS 2012 Causal discovery with scale-mixture model for spatiotemporal variance dependencies NeurIPS 2012 Causality with Gates AISTATS 2012 Cocktail Party Processing via Structured Prediction NeurIPS 2012 Collaborative Gaussian Processes for Preference Learning NeurIPS 2012 Complex Inference in Neural Circuits with Probabilistic Population Codes and Topic Models NeurIPS 2012 Compressive neural representation of sparse, high-dimensional probabilities NeurIPS 2012 Continuous Relaxations for Discrete Hamiltonian Monte Carlo NeurIPS 2012 Copula Network Classifiers (CNCs) AISTATS 2012 Coupling Nonparametric Mixtures via Latent Dirichlet Processes NeurIPS 2012 Cumulative Restricted Boltzmann Machines for Ordinal Matrix Data Analysis ACML 2012 Density-Difference Estimation NeurIPS 2012