maximum likelihood

Maximum Likelihood Learning With Arbitrary Treewidth via Fast-Mixing Parameter Sets NeurIPS 2015 Newton-Stein Method: A Second Order Method for GLMs via Stein's Lemma NeurIPS 2015 Asymptotic Accuracy of Distribution-Based Estimation of Latent Variables JMLR 2014 Clustering from Labels and Time-Varying Graphs NeurIPS 2014 Distributed Estimation, Information Loss and Exponential Families NeurIPS 2014 Influence Function Learning in Information Diffusion Networks ICML 2014 Learning Time-Varying Coverage Functions NeurIPS 2014 Towards Maximum Likelihood: Learning Undirected Graphical Models using Persistent Sequential Monte Carlo ACML 2014 Unbiased Generative Semi-Supervised Learning JMLR 2014 A Max-Norm Constrained Minimization Approach to 1-Bit Matrix Completion JMLR 2013 Convex Relaxations for Learning Bounded-Treewidth Decomposable Graphs ICML 2013 Detecting and Naming Actors in Movies Using Generative Appearance Models CVPR 2013 Learning Gaussian Graphical Models with Observed or Latent FVSs NeurIPS 2013 Robust Matrix Factorization with Unknown Noise ICCV 2013 Spectral methods for neural characterization using generalized quadratic models NeurIPS 2013 Structured Learning via Logistic Regression NeurIPS 2013 An Introduction to Artificial Prediction Markets for Classification JMLR 2012 Iterative Thresholding Algorithm for Sparse Inverse Covariance Estimation NeurIPS 2012 Mixing Properties of Conditional Markov Chains with Unbounded Feature Functions NeurIPS 2012 Multi-Task Averaging NeurIPS 2012 Noise-Contrastive Estimation of Unnormalized Statistical Models, with Applications to Natural Image Statistics JMLR 2012 Random Utility Theory for Social Choice NeurIPS 2012 Sample Complexity of Composite Likelihood AISTATS 2012 Bayesian Spike-Triggered Covariance Analysis NeurIPS 2011 Comparative Analysis of Viterbi Training and Maximum Likelihood Estimation for HMMs NeurIPS 2011