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Bayesian Learning

455 directly classified papers

Papers per year

Papers

Bayesian Agglomerative Clustering with Coalescents NIPS 2007
Infinite State Bayes-Nets for Structured Domains NIPS 2007
A New View of Automatic Relevance Determination NIPS 2007
Regulator Discovery from Gene Expression Time Series of Malaria Parasites: a Hierachical Approach NIPS 2007
Bayesian Image Super-resolution, Continued NIPS 2006
Bayesian Network Learning with Parameter Constraints JMLR 2006
Accelerated Variational Dirichlet Process Mixtures NIPS 2006
Adaptor Grammars: A Framework for Specifying Compositional Nonparametric Bayesian Models NIPS 2006
Context Effects in Category Learning: An Investigation of Four Probabilistic Models NIPS 2006
Learning Time-Intensity Profiles of Human Activity using Non-Parametric Bayesian Models NIPS 2006
Learning to be Bayesian without Supervision 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 Ensemble Learning NIPS 2006
Modeling Dyadic Data with Binary Latent Factors 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
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 Hidden Variable Networks: The Information Bottleneck Approach JMLR 2005