expectation-maximization algorithm

Global Convergence of the EM Algorithm for Mixtures of Two Component Linear Regression COLT 2019 A Bayesian Mixed-Effects Model to Learn Trajectories of Changes from Repeated Manifold-Valued Observations JMLR 2017 High-Dimensional Variance-Reduced Stochastic Gradient Expectation-Maximization Algorithm ICML 2017 Learning spatiotemporal trajectories from manifold-valued longitudinal data NeurIPS 2015 Regularized EM Algorithms: A Unified Framework and Statistical Guarantees NeurIPS 2015 Approximate Gaussian process inference for the drift function in stochastic differential equations NeurIPS 2013 Probabilistic Low-Rank Matrix Completion with Adaptive Spectral Regularization Algorithms NeurIPS 2013 Similarity Component Analysis NeurIPS 2013 Graphlet decomposition of a weighted network AISTATS 2012 Latent Coincidence Analysis: A Hidden Variable Model for Distance Metric Learning NeurIPS 2012 Demixed Principal Component Analysis NeurIPS 2011 An EM Algorithm on BDDs with Order Encoding for Logic-based Probabilistic Models ACML 2010 Fast Large-scale Mixture Modeling with Component-specific Data Partitions NeurIPS 2010 Convex Clustering with Exemplar-Based Models NeurIPS 2007