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Bayesian Learning

1663 directly classified papers

Papers per year

Papers

A Bayesian Approach for Learning and Planning in Partially Observable Markov Decision Processes JMLR 2011
Parallel Algorithm for Learning Optimal Bayesian Network Structure JMLR 2011
A Bayesian Framework for Figure-Ground Interpretation NIPS 2010
PAC-Bayesian Model Selection for Reinforcement Learning NIPS 2010
Slice sampling covariance hyperparameters of latent Gaussian models NIPS 2010
Gaussian Process Preference Elicitation NIPS 2010
Exact learning curves for Gaussian process regression on large random graphs NIPS 2010
PLISS: Detecting and Labeling Places Using Online Change-Point Detection RSS 2010
Real-time Multiattribute Bayesian Preference Elicitation with Pairwise Comparison Queries AISTATS 2010
Near-Optimal Bayesian Active Learning with Noisy Observations NIPS 2010
Shadow Dirichlet for Restricted Probability Modeling NIPS 2010
Continuous Time Bayesian Network Reasoning and Learning Engine JMLR 2010
Optimal Search on Clustered Structural Constraint for Learning Bayesian Network Structure JMLR 2010
Batch Bayesian Optimization via Simulation Matching NIPS 2010
Bayesian variable order Markov models AISTATS 2010
Matrix-Variate Dirichlet Process Mixture Models AISTATS 2010
Dynamic Infinite Relational Model for Time-varying Relational Data Analysis NIPS 2010
Joint Analysis of Time-Evolving Binary Matrices and Associated Documents NIPS 2010
Probabilistic Inference and Differential Privacy NIPS 2010
Probabilistic Deterministic Infinite Automata NIPS 2010
Synergies in learning words and their referents NIPS 2010
Probabilistic latent variable models for distinguishing between cause and effect NIPS 2010
Nonparametric Bayesian Policy Priors for Reinforcement Learning NIPS 2010
Learning the context of a category NIPS 2010
Categories and Functional Units: An Infinite Hierarchical Model for Brain Activations NIPS 2010