parameter estimation

Generalized Inverse Optimization through Online Learning NeurIPS 2018 Geometric Lower Bounds for Distributed Parameter Estimation under Communication Constraints COLT 2018 Graphical Models for Non-Negative Data Using Generalized Score Matching AISTATS 2018 Kernel Recursive ABC: Point Estimation with Intractable Likelihood ICML 2018 Latent RANSAC CVPR 2018 Learning a Mixture of Two Multinomial Logits ICML 2018 Learning Binary Latent Variable Models: A Tensor Eigenpair Approach ICML 2018 Learning Hidden Quantum Markov Models AISTATS 2018 Making Continuous Time Bayesian Networks More Flexible PGM 2018 Maximum Likelihood Estimation for Mixtures of Spherical Gaussians is NP-hard JMLR 2018 Noise Contrastive Estimation and Negative Sampling for Conditional Models: Consistency and Statistical Efficiency EMNLP 2018 On Semiparametric Exponential Family Graphical Models JMLR 2018 Probability–Revealing Samples AISTATS 2018 Sliced Wasserstein Distance for Learning Gaussian Mixture Models CVPR 2018 Statistical Tomography of Microscopic Life CVPR 2018 Theoretical guarantees for EM under misspecified Gaussian mixture models NeurIPS 2018 The Search Problem in Mixture Models JMLR 2018 A Network Framework for Noisy Label Aggregation in Social Media ACL 2017 Binary and Multi-Bit Coding for Stable Random Projections AISTATS 2017 Dense Distributions from Sparse Samples: Improved Gibbs Sampling Parameter Estimators for LDA JMLR 2017 Learning Mixture of Gaussians with Streaming Data NeurIPS 2017 Learning Overcomplete HMMs NeurIPS 2017 Learning Populations of Parameters NeurIPS 2017 Noisy Population Recovery from Unknown Noise COLT 2017 Ordinal Graphical Models: A Tale of Two Approaches ICML 2017