Bayesian Learning

Hybrid Discriminative-Generative Approach with Gaussian Processes AISTATS 2014 Inconsistency of Pitman-Yor Process Mixtures for the Number of Components JMLR 2014 Incremental Local Gaussian Regression NeurIPS 2014 Incremental Tree-Based Inference with Dependent Normalized Random Measures AISTATS 2014 Information-based learning by agents in unbounded state spaces NeurIPS 2014 Learning Modular Structures from Network Data and Node Variables ICML 2014 Learning Optimal Bounded Treewidth Bayesian Networks via Maximum Satisfiability AISTATS 2014 Learning the Irreducible Representations of Commutative Lie Groups ICML 2014 MAP Visibility Estimation for Large-Scale Dynamic 3D Reconstruction CVPR 2014 Max-Margin Infinite Hidden Markov Models ICML 2014 Mind the Nuisance: Gaussian Process Classification using Privileged Noise NeurIPS 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 Online Bayesian Passive-Aggressive Learning ICML 2014 On Prior Distributions and Approximate Inference for Structured Variables NeurIPS 2014 Parallel MCMC with Generalized Elliptical Slice Sampling JMLR 2014 Parallel Sampling of HDPs using Sub-Cluster Splits NeurIPS 2014 Poisson Process Jumping between an Unknown Number of Rates: Application to Neural Spike Data NeurIPS 2014 Positive Curvature and Hamiltonian Monte Carlo NeurIPS 2014 Random Bayesian networks with bounded indegree AISTATS 2014 Robust Bayesian Max-Margin Clustering NeurIPS 2014 Scalable and Robust Bayesian Inference via the Median Posterior ICML 2014