Probabilistic Modeling

The Kernel Beta Process NeurIPS 2011 Thinning Measurement Models and Questionnaire Design NeurIPS 2011 Two is better than one: distinct roles for familiarity and recollection in retrieving palimpsest memories NeurIPS 2011 Unifying Non-Maximum Likelihood Learning Objectives with Minimum KL Contraction NeurIPS 2011 A Discriminative Latent Model of Image Region and Object Tag Correspondence NeurIPS 2010 A generalization of the Multiple-try Metropolis algorithm for Bayesian estimation and model selection AISTATS 2010 An Alternative Prior Process for Nonparametric Bayesian Clustering AISTATS 2010 An EM Algorithm on BDDs with Order Encoding for Logic-based Probabilistic Models ACML 2010 A New Probabilistic Model for Rank Aggregation NeurIPS 2010 A novel family of non-parametric cumulative based divergences for point processes NeurIPS 2010 Approximate Inference by Compilation to Arithmetic Circuits NeurIPS 2010 Approximate inference in continuous time Gaussian-Jump processes NeurIPS 2010 Approximation of hidden Markov models by mixtures of experts with application to particle filtering AISTATS 2010 A Study of Approximate Inference in Probabilistic Relational Models ACML 2010 Auto-Regressive HMM Inference with Incomplete Data for Short-Horizon Wind Forecasting NeurIPS 2010 Bayesian variable order Markov models AISTATS 2010 Brain covariance selection: better individual functional connectivity models using population prior NeurIPS 2010 Collaborative Filtering via Rating Concentration AISTATS 2010 Computing Marginal Distributions over Continuous Markov Networks for Statistical Relational Learning NeurIPS 2010 Construction of Dependent Dirichlet Processes based on Poisson Processes NeurIPS 2010 Copula Bayesian Networks NeurIPS 2010 Dense Message Passing for Sparse Principal Component Analysis AISTATS 2010 Dependent Indian Buffet Processes AISTATS 2010 Deterministic Bayesian inference for the $p*$ model AISTATS 2010 Deterministic Single-Pass Algorithm for LDA NeurIPS 2010