Bayesian & Probabilistic

On Mixtures of Markov Chains NeurIPS 2016 On Pruning with the MDL Score PGM 2016 On Quantile Regression in Reproducing Kernel Hilbert Spaces with the Data Sparsity Constraint JMLR 2016 On Stacking Probabilistic Temporal Models with Bidirectional Information Flow PGM 2016 Optimal Estimation and Completion of Matrices with Biclustering Structures JMLR 2016 Optimistic Gittins Indices NeurIPS 2016 Penalized Maximum Likelihood Estimation of Multi-layered Gaussian Graphical Models JMLR 2016 Poisson-Gamma dynamical systems NeurIPS 2016 Predictive Entropy Search for Multi-objective Bayesian Optimization ICML 2016 Probabilistic Approaches to the AXB = YCZ Calibration Problem in Multi-Robot Systems RSS 2016 Probabilistic Graphical Models Specified by Probabilistic Logic Programs: Semantics and Complexity PGM 2016 Probabilistic Linear Multistep Methods NeurIPS 2016 Probabilistic Low-Rank Matrix Completion from Quantized Measurements JMLR 2016 Probabilistic Prototype Model for Serendipitous Property Mining COLING 2016 Reconstructing Parameters of Spreading Models from Partial Observations NeurIPS 2016 Regime Aware Learning PGM 2016 Regression Methods Applied to Flight Variables for Situational Awareness Estimation Using Dynamic Bayesian Networks PGM 2016 Reintroducing Credal Networks under Epistemic Irrelevance PGM 2016 Relevant Path Separation: A Faster Method for Testing Independencies in Bayesian Networks PGM 2016 Relevant sparse codes with variational information bottleneck NeurIPS 2016 Rényi Divergence Variational Inference NeurIPS 2016 Safe Exploration in Finite Markov Decision Processes with Gaussian Processes NeurIPS 2016 Sampling for Bayesian Program Learning NeurIPS 2016 Scalable Approximate Bayesian Inference for Outlier Detection under Informative Sampling JMLR 2016 Scalable Learning of Bayesian Network Classifiers JMLR 2016