em algorithm

A Method of Moments for Mixture Models and Hidden Markov Models COLT 2012 EP-GIG Priors and Applications in Bayesian Sparse Learning JMLR 2012 Fast Variational Mode-Seeking AISTATS 2012 The variational hierarchical EM algorithm for clustering hidden Markov models NeurIPS 2012 A concave regularization technique for sparse mixture models NeurIPS 2011 Tracking-Based Semi-Supervised Learning RSS 2011 An Approximate Inference Approach to Temporal Optimization in Optimal Control NeurIPS 2010 Fast Large-scale Mixture Modeling with Component-specific Data Partitions NeurIPS 2010 Probabilistic Multi-Task Feature Selection NeurIPS 2010 Variational bounds for mixed-data factor analysis NeurIPS 2010 Learning a Small Mixture of Trees NeurIPS 2009 Policy Search for Motor Primitives in Robotics NeurIPS 2008 Agreement-Based Learning NeurIPS 2007 Learning with Tree-Averaged Densities and Distributions NeurIPS 2007 Penalized Model-Based Clustering with Application to Variable Selection JMLR 2007 An EM Algorithm for Localizing Multiple Sound Sources in Reverberant Environments NeurIPS 2006 Clustering Under Prior Knowledge with Application to Image Segmentation NeurIPS 2006 Non-rigid point set registration: Coherent Point Drift NeurIPS 2006 Parameter Expanded Variational Bayesian Methods NeurIPS 2006 Part-based Probabilistic Point Matching using Equivalence Constraints NeurIPS 2006 Clustering with Bregman Divergences JMLR 2005 Convergence Theorems for Generalized Alternating Minimization Procedures JMLR 2005 Denoising Source Separation JMLR 2005 Learning Hidden Variable Networks: The Information Bottleneck Approach JMLR 2005 The em Algorithm for Kernel Matrix Completion with Auxiliary Data JMLR 2003