Probabilistic Modeling

Divisive Normalization: Justification and Effectiveness as Efficient Coding Transform NeurIPS 2010 Dynamic Infinite Relational Model for Time-varying Relational Data Analysis NeurIPS 2010 Efficient Collapsed Gibbs Sampling for Latent Dirichlet Allocation ACML 2010 Efficient Learning of Deep Boltzmann Machines AISTATS 2010 Efficient Relational Learning with Hidden Variable Detection NeurIPS 2010 Empirical Risk Minimization with Approximations of Probabilistic Grammars NeurIPS 2010 Evaluation of Rarity of Fingerprints in Forensics NeurIPS 2010 Exact inference and learning for cumulative distribution functions on loopy graphs NeurIPS 2010 Extended Bayesian Information Criteria for Gaussian Graphical Models NeurIPS 2010 Focused Belief Propagation for Query-Specific Inference AISTATS 2010 Gated Softmax Classification NeurIPS 2010 Gaussian sampling by local perturbations NeurIPS 2010 Generative Local Metric Learning for Nearest Neighbor Classification NeurIPS 2010 Generative Models of Information Diffusion with Asynchronous Timedelay ACML 2010 Global seismic monitoring as probabilistic inference NeurIPS 2010 Graphical Gaussian modelling of multivariate time series with latent variables AISTATS 2010 Group Sparse Coding with a Laplacian Scale Mixture Prior NeurIPS 2010 Heavy-Tailed Process Priors for Selective Shrinkage NeurIPS 2010 HOP-MAP: Efficient Message Passing with High Order Potentials AISTATS 2010 Identifying Cause and Effect on Discrete Data using Additive Noise Models AISTATS 2010 Implicit encoding of prior probabilities in optimal neural populations NeurIPS 2010 Improvements to the Sequence Memoizer NeurIPS 2010 Improving Human Judgments by Decontaminating Sequential Dependencies NeurIPS 2010 Inference and Learning in Networks of Queues AISTATS 2010 Inference of Sparse Networks with Unobserved Variables. Application to Gene Regulatory Networks AISTATS 2010