Variational Inference

Smoothed Gradients for Stochastic Variational Inference NeurIPS 2014 Stochastic variational inference for hidden Markov models NeurIPS 2014 Subspace Embeddings for the Polynomial Kernel NeurIPS 2014 Tilted Variational Bayes AISTATS 2014 Variational Gaussian Process State-Space Models NeurIPS 2014 Annealing between distributions by averaging moments NeurIPS 2013 Approximate inference in latent Gaussian-Markov models from continuous time observations NeurIPS 2013 Bayesian Canonical Correlation Analysis JMLR 2013 Collapsed Variational Bayesian Inference for Hidden Markov Models AISTATS 2013 Efficient Online Inference for Bayesian Nonparametric Relational Models NeurIPS 2013 Efficient Optimization for Sparse Gaussian Process Regression NeurIPS 2013 Efficient Variational Inference for Gaussian Process Regression Networks AISTATS 2013 Factorized Asymptotic Bayesian Inference for Latent Feature Models NeurIPS 2013 Fast Dual Variational Inference for Non-Conjugate Latent Gaussian Models ICML 2013 Flexible sampling of discrete data correlations without the marginal distributions NeurIPS 2013 Gaussian Process Vine Copulas for Multivariate Dependence ICML 2013 Global Solver and Its Efficient Approximation for Variational Bayesian Low-rank Subspace Clustering NeurIPS 2013 Integrated Non-Factorized Variational Inference NeurIPS 2013 Kernelized Bayesian Matrix Factorization ICML 2013 Learning to Pass Expectation Propagation Messages NeurIPS 2013 Memoized Online Variational Inference for Dirichlet Process Mixture Models NeurIPS 2013 Message passing with l1 penalized KL minimization ICML 2013 Modeling Overlapping Communities with Node Popularities NeurIPS 2013 Online Learning of Nonparametric Mixture Models via Sequential Variational Approximation NeurIPS 2013 Online Variational Approximations to non-Exponential Family Change Point Models: With Application to Radar Tracking NeurIPS 2013