Bayesian Inference

The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo JMLR 2014 Thompson Sampling for Complex Online Problems ICML 2014 Tilted Variational Bayes AISTATS 2014 Towards scaling up Markov chain Monte Carlo: an adaptive subsampling approach ICML 2014 Tree-structured Gaussian Process Approximations NeurIPS 2014 Understanding the Limiting Factors of Topic Modeling via Posterior Contraction Analysis ICML 2014 Using Trajectory Data to Improve Bayesian Optimization for Reinforcement Learning JMLR 2014 Variational Gaussian Inference for Bilinear Models of Count Data ACML 2014 Variational Gaussian Process State-Space Models NeurIPS 2014 Variational Inference for Sequential Distance Dependent Chinese Restaurant Process ICML 2014 Visual Tracking via Probability Continuous Outlier Model CVPR 2014 Von Mises-Fisher Clustering Models ICML 2014 What Regularized Auto-Encoders Learn from the Data-Generating Distribution JMLR 2014 A Bayesian Approach to Multimodal Visual Dictionary Learning CVPR 2013 ABC Reinforcement Learning ICML 2013 Accurate and Robust Registration of Nonrigid Surface Using Hierarchical Statistical Shape Model CVPR 2013 Active Learning for Probabilistic Hypotheses Using the Maximum Gibbs Error Criterion NeurIPS 2013 Active Visual Recognition with Expertise Estimation in Crowdsourcing ICCV 2013 Adaptive Hamiltonian and Riemann Manifold Monte Carlo ICML 2013 Adaptive Sparsity in Gaussian Graphical Models ICML 2013 A Determinantal Point Process Latent Variable Model for Inhibition in Neural Spiking Data NeurIPS 2013 A Graphical Transformation for Belief Propagation: Maximum Weight Matchings and Odd-Sized Cycles NeurIPS 2013 A* Lasso for Learning a Sparse Bayesian Network Structure for Continuous Variables NeurIPS 2013 A Lazy Man's Approach to Benchmarking: Semisupervised Classifier Evaluation and Recalibration CVPR 2013 An Adaptive Learning Rate for Stochastic Variational Inference ICML 2013