Probabilistic Modeling

Joint Probabilistic Matching Using m-Best Solutions CVPR 2016 Joint Structural Estimation of Multiple Graphical Models JMLR 2016 Kernel Mean Shrinkage Estimators JMLR 2016 Kronecker Determinantal Point Processes NeurIPS 2016 Learning and Inference via Maximum Inner Product Search ICML 2016 Learning Complex Uncertain States Changes via Asymmetric Hidden Markov Models: an Industrial Case PGM 2016 Learning Granger Causality for Hawkes Processes ICML 2016 Learning HMMs with Nonparametric Emissions via Spectral Decompositions of Continuous Matrices NeurIPS 2016 Learning Mixtures of Plackett-Luce Models ICML 2016 Learning Planar Ising Models JMLR 2016 Learning Tractable Multidimensional Bayesian Network Classifiers PGM 2016 Local Maxima in the Likelihood of Gaussian Mixture Models: Structural Results and Algorithmic Consequences NeurIPS 2016 Measuring the reliability of MCMC inference with bidirectional Monte Carlo NeurIPS 2016 Memory-Bounded Left-Corner Unsupervised Grammar Induction on Child-Directed Input COLING 2016 Mixture of Bilateral-Projection Two-Dimensional Probabilistic Principal Component Analysis CVPR 2016 Modeling topic dependencies in semantically coherent text spans with copulas COLING 2016 Model Integration for HMM- and DNN-Based Speech Synthesis Using Product-of-Experts Framework Interspeech 2016 Multi-Label Classification with Cutset Networks PGM 2016 Multi-view Anomaly Detection via Robust Probabilistic Latent Variable Models NeurIPS 2016 Natural-Parameter Networks: A Class of Probabilistic Neural Networks NeurIPS 2016 Neurons Equipped with Intrinsic Plasticity Learn Stimulus Intensity Statistics NeurIPS 2016 Non-linear Causal Inference using Gaussianity Measures JMLR 2016 Nonlinear Statistical Learning with Truncated Gaussian Graphical Models ICML 2016 On collapsed representation of hierarchical Completely Random Measures ICML 2016 Online Algorithms for Sum-Product Networks with Continuous Variables PGM 2016