nonparametric estimation

Learning Mixtures of Smooth Product Distributions: Identifiability and Algorithm AISTATS 2019 Least Squares Estimation of Weakly Convex Functions AISTATS 2019 Nearest Neighbor and Kernel Survival Analysis: Nonasymptotic Error Bounds and Strong Consistency Rates ICML 2019 Nonparametric Density Estimation & Convergence Rates for GANs under Besov IPM Losses NeurIPS 2019 Nonparametric Estimation of Probability Density Functions of Random Persistence Diagrams JMLR 2019 Adversarial Time-to-Event Modeling ICML 2018 Bayesian Model Selection for Change Point Detection and Clustering ICML 2018 Derivative Estimation in Random Design NeurIPS 2018 Nonparametric Density Estimation under Adversarial Losses NeurIPS 2018 Nonparametric variable importance using an augmented neural network with multi-task learning ICML 2018 State-by-state Minimax Adaptive Estimation for Nonparametric Hidden {M}arkov Models JMLR 2018 The Nearest Neighbor Information Estimator is Adaptively Near Minimax Rate-Optimal NeurIPS 2018 Topological mixture estimation ICML 2018 Uncovering Causality from Multivariate Hawkes Integrated Cumulants JMLR 2018 Communication-Efficient Distributed Learning of Discrete Distributions NeurIPS 2017 Computational Limits of A Distributed Algorithm for Smoothing Spline JMLR 2017 Density Estimation in Infinite Dimensional Exponential Families JMLR 2017 Higher-Order Total Variation Classes on Grids: Minimax Theory and Trend Filtering Methods NeurIPS 2017 Nonparametrically Trained Probabilistic Linear Discriminant Analysis for i-Vector Speaker Verification Interspeech 2017 Nonparanormal Information Estimation ICML 2017 Online Learning for Multivariate Hawkes Processes NeurIPS 2017 Poisson intensity estimation with reproducing kernels AISTATS 2017 Uncovering Causality from Multivariate Hawkes Integrated Cumulants ICML 2017 Consistent Kernel Mean Estimation for Functions of Random Variables NeurIPS 2016 Efficient Nonparametric Smoothness Estimation NeurIPS 2016