probabilistic modeling

Complexity of Inference in Latent Dirichlet Allocation NeurIPS 2011 Expressive Power and Approximation Errors of Restricted Boltzmann Machines NeurIPS 2011 Generalized Beta Mixtures of Gaussians NeurIPS 2011 Group Anomaly Detection using Flexible Genre Models NeurIPS 2011 Inductive reasoning about chimeric creatures NeurIPS 2011 MAP Inference for Bayesian Inverse Reinforcement Learning NeurIPS 2011 On the Relation between Realizable and Nonrealizable Cases of the Sequence Prediction Problem JMLR 2011 Probabilistic Joint Image Segmentation and Labeling NeurIPS 2011 Probabilistic Modeling of Dependencies Among Visual Short-Term Memory Representations NeurIPS 2011 The Discrete Infinite Logistic Normal Distribution for Mixed-Membership Modeling AISTATS 2011 Unifying Non-Maximum Likelihood Learning Objectives with Minimum KL Contraction NeurIPS 2011 A Bayesian Approach to Concept Drift NeurIPS 2010 A New Probabilistic Model for Rank Aggregation NeurIPS 2010 Computing Marginal Distributions over Continuous Markov Networks for Statistical Relational Learning NeurIPS 2010 Copula Bayesian Networks NeurIPS 2010 Dynamic Infinite Relational Model for Time-varying Relational Data Analysis NeurIPS 2010 Exact learning curves for Gaussian process regression on large random graphs NeurIPS 2010 Group Sparse Coding with a Laplacian Scale Mixture Prior NeurIPS 2010 Improvements to the Sequence Memoizer NeurIPS 2010 Learning concept graphs from text with stick-breaking priors NeurIPS 2010 Learning Efficient Markov Networks NeurIPS 2010 Learning the context of a category NeurIPS 2010 Linear readout from a neural population with partial correlation data NeurIPS 2010 Probabilistic Belief Revision with Structural Constraints NeurIPS 2010 Shadow Dirichlet for Restricted Probability Modeling NeurIPS 2010