Bayesian Inference

The Segmented iHMM: A Simple, Efficient Hierarchical Infinite HMM ICML 2016 Threshold Learning for Optimal Decision Making NeurIPS 2016 Tight Variational Bounds via Random Projections and I-Projections AISTATS 2016 Time-Varying Gaussian Process Bandit Optimization AISTATS 2016 Towards Unifying Hamiltonian Monte Carlo and Slice Sampling NeurIPS 2016 Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set Estimation NeurIPS 2016 Twin Model G-PLDA for Duration Mismatch Compensation in Text-Independent Speaker Verification Interspeech 2016 Uncertainty-Driven 6D Pose Estimation of Objects and Scenes From a Single RGB Image CVPR 2016 Unifying Count-Based Exploration and Intrinsic Motivation NeurIPS 2016 Unsupervised Stress Information Labeling Using Gaussian Process Latent Variable Model for Statistical Speech Synthesis Interspeech 2016 Variance Reduction in Stochastic Gradient Langevin Dynamics NeurIPS 2016 Variational Bayes on Monte Carlo Steroids NeurIPS 2016 Variational Gaussian Copula Inference AISTATS 2016 Variational Inference for Monte Carlo Objectives ICML 2016 Variational Inference in Mixed Probabilistic Submodular Models NeurIPS 2016 Variational Information Maximization for Feature Selection NeurIPS 2016 Variational Tempering AISTATS 2016 VIME: Variational Information Maximizing Exploration NeurIPS 2016 A Bayesian nonparametric procedure for comparing algorithms ICML 2015 A Complete Recipe for Stochastic Gradient MCMC NeurIPS 2015 A Convex Exemplar-based Approach to MAD-Bayes Dirichlet Process Mixture Models ICML 2015 Adaptive Low-Complexity Sequential Inference for Dirichlet Process Mixture Models NeurIPS 2015 A Dirichlet Process Mixture Model for Spherical Data AISTATS 2015 A Fast Variational Approach for Learning Markov Random Field Language Models ICML 2015 A Framework for Individualizing Predictions of Disease Trajectories by Exploiting Multi-Resolution Structure NeurIPS 2015