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Bayesian Learning

1663 directly classified papers

Papers per year

Papers

A Nonparametric Bayesian Approach Toward Stacked Convolutional Independent Component Analysis ICCV 2015
Gamma Processes, Stick-Breaking, and Variational Inference AISTATS 2015
Falling Rule Lists AISTATS 2015
DP-space: Bayesian Nonparametric Subspace Clustering with Small-variance Asymptotics ICML 2015
Concave Penalized Estimation of Sparse Gaussian Bayesian Networks JMLR 2015
Weight Uncertainty in Neural Network ICML 2015
Privacy for Free: Posterior Sampling and Stochastic Gradient Monte Carlo ICML 2015
Distributed Inference for Dirichlet Process Mixture Models ICML 2015
Bayesian Multiple Target Localization ICML 2015
Exponential Integration for Hamiltonian Monte Carlo ICML 2015
Enabling scalable stochastic gradient-based inference for Gaussian processes by employing the Unbiased LInear System SolvEr (ULISSE) ICML 2015
A New Perspective and Extension of the Gaussian Filter RSS 2015
Metadata Dependent Mondrian Processes ICML 2015
Controversy in mechanistic modelling with Gaussian processes ICML 2015
Bayesian and Empirical Bayesian Forests ICML 2015
Scalable Adaptation of State Complexity for Nonparametric Hidden Markov Models NIPS 2015
Non-Gaussian Discriminative Factor Models via the Max-Margin Rank-Likelihood ICML 2015
Reactive bandits with attitude AISTATS 2015
Adaptive Low-Complexity Sequential Inference for Dirichlet Process Mixture Models NIPS 2015
On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators NIPS 2015
Segregated Graphs and Marginals of Chain Graph Models NIPS 2015
Large-Scale Bayesian Multi-Label Learning via Topic-Based Label Embeddings NIPS 2015
Bayesian Non-Parametric Inference for Manifold Based MoCap Representation ICCV 2015
Multi-Class Multi-Annotator Active Learning With Robust Gaussian Process for Visual Recognition ICCV 2015
Bayesian Nonparametric Covariance Regression JMLR 2015