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Bayesian Learning

455 papers

Papers per year

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11
42
10
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Papers

Infinite State Bayes-Nets for Structured Domains NIPS 2007
Multi-Task Learning for Classification with Dirichlet Process Priors JMLR 2007
Integrating Naïve Bayes and FOIL JMLR 2007
"Ideal Parent” Structure Learning for Continuous Variable Bayesian Networks JMLR 2007
Bayesian Image Super-resolution, Continued NIPS 2006
Bayesian Ensemble Learning NIPS 2006
Modeling Dyadic Data with Binary Latent Factors NIPS 2006
Accelerated Variational Dirichlet Process Mixtures NIPS 2006
A Nonparametric Bayesian Method for Inferring Features From Similarity Judgments NIPS 2006
Hierarchical Dirichlet Processes with Random Effects NIPS 2006
Particle Filtering for Nonparametric Bayesian Matrix Factorization NIPS 2006
Tighter PAC-Bayes Bounds NIPS 2006
Dirichlet-Enhanced Spam Filtering based on Biased Samples NIPS 2006
Bayesian Policy Gradient Algorithms NIPS 2006
Adaptor Grammars: A Framework for Specifying Compositional Nonparametric Bayesian Models NIPS 2006
Data Integration for Classification Problems Employing Gaussian Process Priors NIPS 2006
PAC-Bayes Bounds for the Risk of the Majority Vote and the Variance of the Gibbs Classifier NIPS 2006
Learning Time-Intensity Profiles of Human Activity using Non-Parametric Bayesian Models NIPS 2006
Learning to be Bayesian without Supervision NIPS 2006
Context Effects in Category Learning: An Investigation of Four Probabilistic Models NIPS 2006
Learning Structural Equation Models for fMRI NIPS 2006
A PAC-Bayes Risk Bound for General Loss Functions NIPS 2006
Relational Learning with Gaussian Processes NIPS 2006
Bayesian Network Learning with Parameter Constraints JMLR 2006
Learning Hidden Variable Networks: The Information Bottleneck Approach JMLR 2005