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Bayesian Learning

1663 directly classified papers

Papers per year

Papers

K2-ABC: Approximate Bayesian Computation with Kernel Embeddings AISTATS 2016
An Information-Theoretic Analysis of Thompson Sampling JMLR 2016
Improving Structure MCMC for Bayesian Networks through Markov Blanket Resampling JMLR 2016
Bayesian Optimization for Likelihood-Free Inference of Simulator-Based Statistical Models JMLR 2016
Bayesian group factor analysis with structured sparsity JMLR 2016
Nonparametric Network Models for Link Prediction JMLR 2016
Bayesian Graphical Models for Multivariate Functional Data JMLR 2016
On Pruning with the MDL Score PGM 2016
Bayesian Torrent Classification by File Name and Size Only PGM 2016
Student Skill Models in Adaptive Testing PGM 2016
An Empirical-Bayes Score for Discrete Bayesian Networks PGM 2016
A Genetic Algorithm for Learning Parameters in Bayesian Networks using Expectation Maximization PGM 2016
Analysis of Variational Bayesian Factorizations for Sparse and Low-Rank Estimation ICML 2016
Dirichlet Process Mixture Model for Correcting Technical Variation in Single-Cell Gene Expression Data ICML 2016
The Knowledge Gradient for Sequential Decision Making with Stochastic Binary Feedbacks ICML 2016
Bayesian Poisson Tucker Decomposition for Learning the Structure of International Relations ICML 2016
Online Learning With Bayesian Classification Trees CVPR 2016
Learning Weight Uncertainty With Stochastic Gradient MCMC for Shape Classification CVPR 2016
Compressing Bayes Net CPTs with Persistent Leaky Causes PGM 2016
Learning Complex Uncertain States Changes via Asymmetric Hidden Markov Models: an Industrial Case PGM 2016
Online Algorithms for Sum-Product Networks with Continuous Variables PGM 2016
Regime Aware Learning PGM 2016
Learning Tractable Multidimensional Bayesian Network Classifiers PGM 2016
Bayesian Matrix Factorization with Non-Random Missing Data using Informative Gaussian Process Priors and Soft Evidences PGM 2016
Bayesian Networks: a Combined Tuning Heuristic PGM 2016