Bayesian Learning

Copula variational inference NeurIPS 2015 Dependent Multinomial Models Made Easy: Stick-Breaking with the Polya-gamma Augmentation NeurIPS 2015 Distributed Inference for Dirichlet Process Mixture Models ICML 2015 DP-space: Bayesian Nonparametric Subspace Clustering with Small-variance Asymptotics ICML 2015 Enabling scalable stochastic gradient-based inference for Gaussian processes by employing the Unbiased LInear System SolvEr (ULISSE) ICML 2015 End-to-end Learning of LDA by Mirror-Descent Back Propagation over a Deep Architecture NeurIPS 2015 Exact Bayesian Learning of Ancestor Relations in Bayesian Networks AISTATS 2015 Exponential Integration for Hamiltonian Monte Carlo ICML 2015 Face Alignment Using Cascade Gaussian Process Regression Trees CVPR 2015 Falling Rule Lists AISTATS 2015 Frank-Wolfe Bayesian Quadrature: Probabilistic Integration with Theoretical Guarantees NeurIPS 2015 Gamma Processes, Stick-Breaking, and Variational Inference AISTATS 2015 Gradient-free Hamiltonian Monte Carlo with Efficient Kernel Exponential Families NeurIPS 2015 Infinite Factorial Dynamical Model NeurIPS 2015 Large-Scale Bayesian Multi-Label Learning via Topic-Based Label Embeddings NeurIPS 2015 Large-scale Distributed Dependent Nonparametric Trees ICML 2015 Latent feature regression for multivariate count data AISTATS 2015 Learning Bayesian Networks with Thousands of Variables NeurIPS 2015 Learning spatiotemporal trajectories from manifold-valued longitudinal data NeurIPS 2015 Manifold-valued Dirichlet Processes ICML 2015 Metadata Dependent Mondrian Processes ICML 2015 Multi-Class Multi-Annotator Active Learning With Robust Gaussian Process for Visual Recognition ICCV 2015 Multi-Feature Max-Margin Hierarchical Bayesian Model for Action Recognition CVPR 2015 Non-Gaussian Discriminative Factor Models via the Max-Margin Rank-Likelihood ICML 2015 Nonparametric Bayesian Factor Analysis for Dynamic Count Matrices AISTATS 2015