maximum likelihood estimation

Leveraging the Exact Likelihood of Deep Latent Variable Models NeurIPS 2018 Maximum Likelihood Estimation for Mixtures of Spherical Gaussians is NP-hard JMLR 2018 Near-Optimal Sample Complexity Bounds for Maximum Likelihood Estimation of Multivariate Log-concave Densities COLT 2018 Neural Math Word Problem Solver with Reinforcement Learning COLING 2018 Nonparametric Sharpe Ratio Function Estimation in Heteroscedastic Regression Models via Convex Optimization AISTATS 2018 Ranking Distributions based on Noisy Sorting ICML 2018 SEARNN: Training RNNs with global-local losses ICLR 2018 Teacher Improves Learning by Selecting a Training Subset AISTATS 2018 A Maximum Likelihood Approach to Deep Neural Network Based Nonlinear Spectral Mapping for Single-Channel Speech Separation Interspeech 2017 A Unified Maximum Likelihood Approach for Estimating Symmetric Properties of Discrete Distributions ICML 2017 Generative Hierarchical Learning of Sparse FRAME Models CVPR 2017 On the Duration of Mandarin Tones Interspeech 2017 Provably Optimal Algorithms for Generalized Linear Contextual Bandits ICML 2017 Regularized Estimation and Testing for High-Dimensional Multi-Block Vector-Autoregressive Models JMLR 2017 Removing Phase Transitions from Gibbs Measures AISTATS 2017 Sequence Tutor: Conservative Fine-Tuning of Sequence Generation Models with KL-control ICML 2017 Ten Steps of EM Suffice for Mixtures of Two Gaussians COLT 2017 A Unified Approach for Learning the Parameters of Sum-Product Networks NeurIPS 2016 Bethe Learning of Graphical Models via MAP Decoding AISTATS 2016 Conditional Probability Estimation PGM 2016 Convergence of an Alternating Maximization Procedure JMLR 2016 Learning Additive Exponential Family Graphical Models via ℓ_2,1-norm Regularized M-Estimation NeurIPS 2016 Learning Infinite RBMs with Frank-Wolfe NeurIPS 2016 Newton-Stein Method: An Optimization Method for GLMs via Stein's Lemma JMLR 2016 Optimal Statistical and Computational Rates for One Bit Matrix Completion AISTATS 2016