Bayesian Inference

Reliable and Scalable Variational Inference for the Hierarchical Dirichlet Process AISTATS 2015 Reweighted Laplace Prior Based Hyperspectral Compressive Sensing for Unknown Sparsity CVPR 2015 Risk and Regret of Hierarchical Bayesian Learners ICML 2015 Risk Bounds for the Majority Vote: From a PAC-Bayesian Analysis to a Learning Algorithm JMLR 2015 Robust Nonrigid Registration by Convex Optimization ICCV 2015 Scalable Adaptation of State Complexity for Nonparametric Hidden Markov Models NeurIPS 2015 Scalable Bayesian Optimization Using Deep Neural Networks ICML 2015 Scalable Deep Poisson Factor Analysis for Topic Modeling ICML 2015 Scalable Inference for Gaussian Process Models with Black-Box Likelihoods NeurIPS 2015 Scalable Nonparametric Multiway Data Analysis AISTATS 2015 Scalable Variational Gaussian Process Classification AISTATS 2015 Scalable Variational Inference in Log-supermodular Models ICML 2015 Scaling up Natural Gradient by Sparsely Factorizing the Inverse Fisher Matrix ICML 2015 Semantically-Aware Aerial Reconstruction From Multi-Modal Data ICCV 2015 Sensor Selection for Crowdsensing Dynamical Systems AISTATS 2015 Small-Variance Nonparametric Clustering on the Hypersphere CVPR 2015 Softstar: Heuristic-Guided Probabilistic Inference NeurIPS 2015 Sparse Variational Inference for Generalized GP Models ICML 2015 State Space Methods for Efficient Inference in Student-t Process Regression AISTATS 2015 Statistical Decision Making for Optimal Budget Allocation in Crowd Labeling JMLR 2015 Stochastic Expectation Propagation NeurIPS 2015 Stochastic Structured Variational Inference AISTATS 2015 Streaming, Distributed Variational Inference for Bayesian Nonparametrics NeurIPS 2015 Streaming Variational Inference for Bayesian Nonparametric Mixture Models AISTATS 2015 Streaming Variational Inference for Dirichlet Process Mixtures ACML 2015