Bayesian Inference

Learning with Maximum A-Posteriori Perturbation Models AISTATS 2014 Locally Adaptive Factor Processes for Multivariate Time Series JMLR 2014 Loopy Belief Propagation in the Presence of Determinism AISTATS 2014 Lower Bounds for the Gibbs Sampler over Mixtures of Gaussians ICML 2014 Making Pairwise Binary Graphical Models Attractive NeurIPS 2014 Memory (and Time) Efficient Sequential Monte Carlo ICML 2014 Modeling High-Dimensional Humans for Activity Anticipation using Gaussian Process Latent CRFs RSS 2014 Multiview Shape and Reflectance from Natural Illumination CVPR 2014 Near Optimal Bayesian Active Learning for Decision Making AISTATS 2014 Neurons as Monte Carlo Samplers: Bayesian Inference and Learning in Spiking Networks NeurIPS 2014 New Rules for Domain Independent Lifted MAP Inference NeurIPS 2014 Nonmyopic ε-Bayes-Optimal Active Learning of Gaussian Processes ICML 2014 Non-Parametric Bayesian Constrained Local Models CVPR 2014 Nonparametric Bayesian inference on multivariate exponential families NeurIPS 2014 On correlation and budget constraints in model-based bandit optimization with application to automatic machine learning AISTATS 2014 Online Bayesian Passive-Aggressive Learning ICML 2014 Online Object Tracking, Learning and Parsing with And-Or Graphs CVPR 2014 On Prior Distributions and Approximate Inference for Structured Variables NeurIPS 2014 On the Bayes-Optimality of F-Measure Maximizers JMLR 2014 Optimal Decisions from Probabilistic Models: The Intersection-over-Union Case CVPR 2014 Optimal prior-dependent neural population codes under shared input noise NeurIPS 2014 PAC-Bayesian AUC classification and scoring NeurIPS 2014 PAC-Bayesian Collective Stability AISTATS 2014 PAC-Bayesian Theory for Transductive Learning AISTATS 2014 Pan-sharpening with a Bayesian nonparametric dictionary learning model AISTATS 2014