Bayesian & Probabilistic

Efficient Bayesian Inference for Dynamically Changing Graphs NeurIPS 2007 Efficient multiple hyperparameter learning for log-linear models NeurIPS 2007 Efficient Principled Learning of Thin Junction Trees NeurIPS 2007 Estimating disparity with confidence from energy neurons NeurIPS 2007 Evaluating Search Engines by Modeling the Relationship Between Relevance and Clicks NeurIPS 2007 Expectation Maximization and Posterior Constraints NeurIPS 2007 Experience-Guided Search: A Theory of Attentional Control NeurIPS 2007 Exponential Family Predictive Representations of State NeurIPS 2007 Fast Variational Inference for Large-scale Internet Diagnosis NeurIPS 2007 Fixing Max-Product: Convergent Message Passing Algorithms for MAP LP-Relaxations NeurIPS 2007 Gaussian Beam Processes: A Nonparametric Bayesian Measurement Model for Range Finders RSS 2007 Gaussian Process Models for Link Analysis and Transfer Learning NeurIPS 2007 GRIFT: A graphical model for inferring visual classification features from human data NeurIPS 2007 Heterogeneous Component Analysis NeurIPS 2007 Hidden Common Cause Relations in Relational Learning NeurIPS 2007 "Ideal Parent” Structure Learning for Continuous Variable Bayesian Networks JMLR 2007 Inferring Elapsed Time from Stochastic Neural Processes NeurIPS 2007 Inferring Neural Firing Rates from Spike Trains Using Gaussian Processes NeurIPS 2007 Infinite State Bayes-Nets for Structured Domains NeurIPS 2007 Integrating Naïve Bayes and FOIL JMLR 2007 Learning Horizontal Connections in a Sparse Coding Model of Natural Images NeurIPS 2007 Learning with Tree-Averaged Densities and Distributions NeurIPS 2007 Loop Corrections for Approximate Inference on Factor Graphs JMLR 2007 Loop Series and Bethe Variational Bounds in Attractive Graphical Models NeurIPS 2007 Markov Chain Monte Carlo with People NeurIPS 2007