Bayesian & Probabilistic

The Mixing of Markov Chains on Linear Extensions in Practice IJCAI 2017 Thompson Sampling for Linear-Quadratic Control Problems AISTATS 2017 Thompson Sampling for the MNL-Bandit COLT 2017 Time-dependent spatially varying graphical models, with application to brain fMRI data analysis NeurIPS 2017 Time for a Change: a Tutorial for Comparing Multiple Classifiers Through Bayesian Analysis JMLR 2017 Unified Representation and Lifted Sampling for Generative Models of Social Networks IJCAI 2017 Universal Reinforcement Learning Algorithms: Survey and Experiments IJCAI 2017 Unsupervised Text Segmentation Based on Native Language Characteristics ACL 2017 Uprooting and Rerooting Higher-Order Graphical Models NeurIPS 2017 Using Graphs of Classifiers to Impose Declarative Constraints on Semi-supervised Learning IJCAI 2017 Variational Autoencoded Regression: High Dimensional Regression of Visual Data on Complex Manifold CVPR 2017 Variational Inference via χ Upper Bound Minimization NeurIPS 2017 Variational Mixtures of Gaussian Processes for Classification IJCAI 2017 Weighted Model Integration with Orthogonal Transformations IJCAI 2017 Zero-Inflated Exponential Family Embeddings ICML 2017 A Bayesian method for reducing bias in neural representational similarity analysis NeurIPS 2016 A Bayesian model for joint word alignment and part-of-speech transfer COLING 2016 Achieving budget-optimality with adaptive schemes in crowdsourcing NeurIPS 2016 A Field Model for Repairing 3D Shapes CVPR 2016 A Fixed-Point Operator for Inference in Variational Bayesian Latent Gaussian Models AISTATS 2016 A Genetic Algorithm for Learning Parameters in Bayesian Networks using Expectation Maximization PGM 2016 A Gibbs Sampler for Learning DAGs JMLR 2016 A Joint Sentiment-Target-Stance Model for Stance Classification in Tweets COLING 2016 Analysis of Variational Bayesian Factorizations for Sparse and Low-Rank Estimation ICML 2016 An Empirical-Bayes Score for Discrete Bayesian Networks PGM 2016