Bayesian & Probabilistic

The Parallel Knowledge Gradient Method for Batch Bayesian Optimization NeurIPS 2016 Threshold Learning for Optimal Decision Making NeurIPS 2016 Tight Variational Bounds via Random Projections and I-Projections AISTATS 2016 Topic-Based Embeddings for Learning from Large Knowledge Graphs AISTATS 2016 Towards Unifying Hamiltonian Monte Carlo and Slice Sampling NeurIPS 2016 Tractable Operations for Arithmetic Circuits of Probabilistic Models 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 Unifying Topic, Sentiment & Preference in an HDP-Based Rating Regression Model for Online Reviews ACML 2016 Uprooting and Rerooting Graphical Models ICML 2016 Using Social Dynamics to Make Individual Predictions: Variational Inference with a Stochastic Kinetic Model NeurIPS 2016 Variable Elimination in the Fourier Domain ICML 2016 Variance Reduction in Stochastic Gradient Langevin Dynamics NeurIPS 2016 Variational Bayes on Monte Carlo Steroids NeurIPS 2016 Variational Inference in Mixed Probabilistic Submodular Models NeurIPS 2016 Variational Tempering AISTATS 2016 Visual Path Prediction in Complex Scenes With Crowded Moving Objects CVPR 2016 Voice Conversion Based on Matrix Variate Gaussian Mixture Model Using Multiple Frame Features Interspeech 2016 What's Wrong With That Object? Identifying Images of Unusual Objects by Modelling the Detection Score Distribution CVPR 2016 A Bayesian Framework for Modeling Confidence in Perceptual Decision Making NeurIPS 2015 Accurate and conservative estimates of MRF log-likelihood using reverse annealing AISTATS 2015 A class of network models recoverable by spectral clustering NeurIPS 2015 A Complete Recipe for Stochastic Gradient MCMC NeurIPS 2015 Adaptive Belief Propagation ICML 2015 Adaptive Low-Complexity Sequential Inference for Dirichlet Process Mixture Models NeurIPS 2015