Bayesian Learning

Bayesian Active Contours with Affine-Invariant, Elastic Shape Prior CVPR 2014 Bayesian Co-Boosting for Multi-modal Gesture Recognition JMLR 2014 Bayesian Inference for Structured Spike and Slab Priors NeurIPS 2014 Bayesian Inference with Posterior Regularization and Applications to Infinite Latent SVMs JMLR 2014 Bayesian Logistic Gaussian Process Models for Dynamic Networks AISTATS 2014 Bayesian Nonlinear Support Vector Machines and Discriminative Factor Modeling NeurIPS 2014 Bayesian Nonparametric Comorbidity Analysis of Psychiatric Disorders JMLR 2014 Bayesian Nonparametric Poisson Factorization for Recommendation Systems AISTATS 2014 Bayesian Sampling Using Stochastic Gradient Thermostats NeurIPS 2014 Beta-Negative Binomial Process and Exchangeable Random Partitions for Mixed-Membership Modeling NeurIPS 2014 Beta Process Multiple Kernel Learning CVPR 2014 Causal Inference through a Witness Protection Program NeurIPS 2014 Cold-start Active Learning with Robust Ordinal Matrix Factorization ICML 2014 Congruency-Based Reranking CVPR 2014 Decoupled Variational Gaussian Inference NeurIPS 2014 Dependent nonparametric trees for dynamic hierarchical clustering NeurIPS 2014 Distance-Based Network Recovery under Feature Correlation NeurIPS 2014 Expectation Backpropagation: Parameter-Free Training of Multilayer Neural Networks with Continuous or Discrete Weights NeurIPS 2014 Expectation Propagation for Neural Networks with Sparsity-Promoting Priors JMLR 2014 Extended and Unscented Gaussian Processes NeurIPS 2014 Gaussian Processes for Bayesian Estimation in Ordinary Differential Equations ICML 2014 Gaussian Process Volatility Model NeurIPS 2014 General Table Completion using a Bayesian Nonparametric Model NeurIPS 2014 Gibbs Max-margin Topic Models with Data Augmentation JMLR 2014 Hamming Ball Auxiliary Sampling for Factorial Hidden Markov Models NeurIPS 2014