Probabilistic Modeling

Color Transfer Using Probabilistic Moving Least Squares CVPR 2014 Compressive Sensing of Signals from a GMM with Sparse Precision Matrices NeurIPS 2014 Concavity of reweighted Kikuchi approximation NeurIPS 2014 Conditional Random Field with High-order Dependencies for Sequence Labeling and Segmentation JMLR 2014 Content-based recommendations with Poisson factorization NeurIPS 2014 Covariance shrinkage for autocorrelated data NeurIPS 2014 Covariance Trees for 2D and 3D Processing CVPR 2014 Dirichlet-based Histogram Feature Transform for Image Classification CVPR 2014 Distance-Based Network Recovery under Feature Correlation NeurIPS 2014 Distributed Estimation, Information Loss and Exponential Families NeurIPS 2014 Distributed Parameter Estimation in Probabilistic Graphical Models NeurIPS 2014 Diverse Sequential Subset Selection for Supervised Video Summarization NeurIPS 2014 Edge Label Inference in Generalized Stochastic Block Models: from Spectral Theory to Impossibility Results COLT 2014 Effective Sampling and Learning for Mallows Models with Pairwise-Preference Data JMLR 2014 Efficient Inference for Complex Queries on Complex Distributions AISTATS 2014 Efficient Inference of Continuous Markov Random Fields with Polynomial Potentials NeurIPS 2014 Efficient Nonlinear Markov Models for Human Motion CVPR 2014 Elementary Estimators for Graphical Models NeurIPS 2014 Estimating Latent-Variable Graphical Models using Moments and Likelihoods ICML 2014 Exchangeable Variable Models ICML 2014 Expectation-Maximization for Learning Determinantal Point Processes NeurIPS 2014 Expectation Propagation for Likelihoods Depending on an Inner Product of Two Multivariate Random Variables AISTATS 2014 Exploiting the Limits of Structure Learning via Inherent Symmetry AISTATS 2014 Extended and Unscented Gaussian Processes NeurIPS 2014 Extracting Latent Structure From Multiple Interacting Neural Populations NeurIPS 2014