parameter estimation

A General Linear Non-Gaussian State-Space Model: Identifiability, Identification, and Applications ACML 2011 Automated Refinement of Bayes Networks' Parameters based on Test Ordering Constraints NeurIPS 2011 Comparative Analysis of Viterbi Training and Maximum Likelihood Estimation for HMMs NeurIPS 2011 Learning Attribute-weighted Voter Model over Social Networks ACML 2011 Learning mixtures of Gaussians with maximum-a-posteriori oracle AISTATS 2011 Mixed Cumulative Distribution Networks AISTATS 2011 Neural Reconstruction with Approximate Message Passing (NeuRAMP) NeurIPS 2011 Sparse Recovery with Brownian Sensing NeurIPS 2011 A Dirty Model for Multi-task Learning NeurIPS 2010 Deterministic Bayesian inference for the $p*$ model AISTATS 2010 Identifying Dendritic Processing NeurIPS 2010 Inference and Learning in Networks of Queues AISTATS 2010 Learning with Blocks: Composite Likelihood and Contrastive Divergence AISTATS 2010 Noise-contrastive estimation: A new estimation principle for unnormalized statistical models AISTATS 2010 On the Convergence Properties of Contrastive Divergence AISTATS 2010 Semi-Supervised Learning with Adversarially Missing Label Information NeurIPS 2010 Shadow Dirichlet for Restricted Probability Modeling NeurIPS 2010 Identification of Recurrent Neural Networks by Bayesian Interrogation Techniques JMLR 2009 Robustness of the Unscented Kalman filter for state and parameter estimation in an elastic transmission RSS 2009 Sensitivity analysis in HMMs with application to likelihood maximization NeurIPS 2009 Using the distribution theory to simultaneously calibrate the sensors of a mobile robot RSS 2009 Agreement-Based Learning NeurIPS 2007 A Probabilistic Analysis of EM for Mixtures of Separated, Spherical Gaussians JMLR 2007 Continuous Time Particle Filtering for fMRI NeurIPS 2007 Discriminative K-means for Clustering NeurIPS 2007