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Bayesian Learning

1663 directly classified papers

Papers per year

Papers

Nonmyopic ε-Bayes-Optimal Active Learning of Gaussian Processes ICML 2014
Online Bayesian Passive-Aggressive Learning ICML 2014
Max-Margin Infinite Hidden Markov Models ICML 2014
Incremental Tree-Based Inference with Dependent Normalized Random Measures AISTATS 2014
Bayesian Nonparametric Comorbidity Analysis of Psychiatric Disorders JMLR 2014
Inconsistency of Pitman-Yor Process Mixtures for the Number of Components JMLR 2014
Bayesian Co-Boosting for Multi-modal Gesture Recognition JMLR 2014
Parallel MCMC with Generalized Elliptical Slice Sampling JMLR 2014
Expectation Propagation for Neural Networks with Sparsity-Promoting Priors JMLR 2014
Bayesian Nonparametric Poisson Factorization for Recommendation Systems AISTATS 2014
Adaptive Variable Clustering in Gaussian Graphical Models AISTATS 2014
SMERED: A Bayesian Approach to Graphical Record Linkage and De-duplication AISTATS 2014
Extended and Unscented Gaussian Processes NIPS 2014
Bayesian Inference for Structured Spike and Slab Priors NIPS 2014
Information-based learning by agents in unbounded state spaces NIPS 2014
Variational Gaussian Process State-Space Models NIPS 2014
Tree-structured Gaussian Process Approximations NIPS 2014
Poisson Process Jumping between an Unknown Number of Rates: Application to Neural Spike Data NIPS 2014
Automated Variational Inference for Gaussian Process Models NIPS 2014
Parallel Sampling of HDPs using Sub-Cluster Splits NIPS 2014
Bayes-Adaptive Simulation-based Search with Value Function Approximation NIPS 2014
Stochastic variational inference for hidden Markov models NIPS 2014
A Bayesian model for identifying hierarchically organised states in neural population activity NIPS 2014
MAP Visibility Estimation for Large-Scale Dynamic 3D Reconstruction CVPR 2014
Neurons as Monte Carlo Samplers: Bayesian Inference and Learning in Spiking Networks NIPS 2014