Bayesian & Probabilistic

Robust Inverse Covariance Estimation under Noisy Measurements ICML 2014 Robust learning of inhomogeneous PMMs AISTATS 2014 Robust Principal Component Analysis with Complex Noise ICML 2014 Sample Efficient Reinforcement Learning with Gaussian Processes ICML 2014 Sampling for Inference in Probabilistic Models with Fast Bayesian Quadrature NeurIPS 2014 Scalable Bayesian Low-Rank Decomposition of Incomplete Multiway Tensors ICML 2014 Scalable Collaborative Bayesian Preference Learning AISTATS 2014 Scalable Variational Bayesian Matrix Factorization with Side Information AISTATS 2014 Scaling Nonparametric Bayesian Inference via Subsample-Annealing AISTATS 2014 Scaling-up Importance Sampling for Markov Logic Networks NeurIPS 2014 Semi-Separable Hamiltonian Monte Carlo for Inference in Bayesian Hierarchical Models NeurIPS 2014 Semi-supervised Learning with Deep Generative Models NeurIPS 2014 Semi-supervised Relational Topic Model for Weakly Annotated Image Recognition in Social Media CVPR 2014 Sensory Integration and Density Estimation NeurIPS 2014 Sequential Monte Carlo for Graphical Models NeurIPS 2014 Shaping Social Activity by Incentivizing Users NeurIPS 2014 Signal Aggregate Constraints in Additive Factorial HMMs, with Application to Energy Disaggregation NeurIPS 2014 Smoothed Gradients for Stochastic Variational Inference NeurIPS 2014 Sparse Bayesian structure learning with “dependent relevance determination” priors NeurIPS 2014 Spatio-temporal Representations of Uncertainty in Spiking Neural Networks NeurIPS 2014 Spectral Learning of Mixture of Hidden Markov Models NeurIPS 2014 Spectral Methods for Indian Buffet Process Inference NeurIPS 2014 Spectral Methods for Supervised Topic Models NeurIPS 2014 Spectral Methods meet EM: A Provably Optimal Algorithm for Crowdsourcing NeurIPS 2014 Spherical Hamiltonian Monte Carlo for Constrained Target Distributions ICML 2014