maximum likelihood estimation

Parameter Estimation for Generalized Thurstone Choice Models ICML 2016 Penalized Maximum Likelihood Estimation of Multi-layered Gaussian Graphical Models JMLR 2016 Quantized Random Projections and Non-Linear Estimation of Cosine Similarity NeurIPS 2016 Relationship between PreTraining and Maximum Likelihood Estimation in Deep Boltzmann Machines AISTATS 2016 Statistical-Computational Tradeoffs in Planted Problems and Submatrix Localization with a Growing Number of Clusters and Submatrices JMLR 2016 Alternating Minimization for Regression Problems with Vector-valued Outputs NeurIPS 2015 Closed-form Estimators for High-dimensional Generalized Linear Models NeurIPS 2015 Consistent estimation of dynamic and multi-layer block models ICML 2015 Convergence Rates of Active Learning for Maximum Likelihood Estimation NeurIPS 2015 Convolutional spike-triggered covariance analysis for neural subunit models NeurIPS 2015 Empirical Localization of Homogeneous Divergences on Discrete Sample Spaces NeurIPS 2015 Fast and Accurate Inference of Plackett–Luce Models NeurIPS 2015 Fixed-point algorithms for learning determinantal point processes ICML 2015 Human Memory Search as Initial-Visit Emitting Random Walk NeurIPS 2015 Newton-Stein Method: A Second Order Method for GLMs via Stein's Lemma NeurIPS 2015 Robust RGB-D Odometry Using Point and Line Features ICCV 2015 Spectral MLE: Top-K Rank Aggregation from Pairwise Comparisons ICML 2015 Clustering from Labels and Time-Varying Graphs NeurIPS 2014 Distributed Estimation, Information Loss and Exponential Families NeurIPS 2014 Elementary Estimators for Graphical Models NeurIPS 2014 Expectation-Maximization for Learning Determinantal Point Processes NeurIPS 2014 Learning Time-Varying Coverage Functions NeurIPS 2014 Minimax-optimal Inference from Partial Rankings NeurIPS 2014 Non-Asymptotic Analysis of Relational Learning with One Network AISTATS 2014 Open Problem: Tightness of maximum likelihood semidefinite relaxations COLT 2014