Bayesian & Probabilistic

An Unsupervised Decontamination Procedure For Improving The Reliability Of Human Judgments NeurIPS 2011 Approximate inference for the loss-calibrated Bayesian AISTATS 2011 Automated Refinement of Bayes Networks' Parameters based on Test Ordering Constraints NeurIPS 2011 Bagged Structure Learning of Bayesian Network AISTATS 2011 Bayesian Bias Mitigation for Crowdsourcing NeurIPS 2011 Bayesian Hierarchical Cross-Clustering AISTATS 2011 Bayesian Inference for Statistical Abduction Using Markov Chain Monte Carlo ACML 2011 Bayesian Partitioning of Large-Scale Distance Data NeurIPS 2011 Bayesian Spike-Triggered Covariance Analysis NeurIPS 2011 Bounds on Individual Risk for Log-loss Predictors COLT 2011 Clustering via Dirichlet Process Mixture Models for Portable Skill Discovery NeurIPS 2011 Collaborative Filtering with the Trace Norm: Learning, Bounding, and Transducing COLT 2011 Collective Graphical Models NeurIPS 2011 Comparative Analysis of Viterbi Training and Maximum Likelihood Estimation for HMMs NeurIPS 2011 Complexity of Inference in Latent Dirichlet Allocation NeurIPS 2011 Concave Gaussian Variational Approximations for Inference in Large-Scale Bayesian Linear Models AISTATS 2011 Confidence Sets for Network Structure NeurIPS 2011 Contextual Gaussian Process Bandit Optimization NeurIPS 2011 Convergent Decomposition Solvers for Tree-reweighted Free Energies AISTATS 2011 Crowdclustering NeurIPS 2011 Demixed Principal Component Analysis NeurIPS 2011 Dependent Hierarchical Beta Process for Image Interpolation and Denoising AISTATS 2011 Dynamical segmentation of single trials from population neural data NeurIPS 2011 Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials NeurIPS 2011 Efficient inference in matrix-variate Gaussian models with \iid observation noise NeurIPS 2011