nonparametric estimation

Finite-Sample Analysis of Fixed-k Nearest Neighbor Density Functional Estimators NeurIPS 2016 Learning HMMs with Nonparametric Emissions via Spectral Decompositions of Continuous Matrices NeurIPS 2016 Minimax Adaptive Estimation of Nonparametric Hidden Markov Models JMLR 2016 Direct Density-Derivative Estimation and Its Application in KL-Divergence Approximation AISTATS 2015 Efficient Estimation of Mutual Information for Strongly Dependent Variables AISTATS 2015 Nonparametric von Mises Estimators for Entropies, Divergences and Mutual Informations NeurIPS 2015 Bias Reduction and Metric Learning for Nearest-Neighbor Estimation of Kullback-Leibler Divergence AISTATS 2014 Nonparametric estimation and testing of exchangeable graph models AISTATS 2014 Nonparametric Estimation of Multi-View Latent Variable Models ICML 2014 Nonparametric Estimation of Renyi Divergence and Friends ICML 2014 Quantized Estimation of Gaussian Sequence Models in Euclidean Balls NeurIPS 2014 Robust Kernel Density Estimation by Scaling and Projection in Hilbert Space NeurIPS 2014 Consistency of Robust Kernel Density Estimators COLT 2013 Data-driven covariate selection for nonparametric estimation of causal effects AISTATS 2013 Density estimation from unweighted k-nearest neighbor graphs: a roadmap NeurIPS 2013 Estimation of Extreme Values and Associated Level Sets of a Regression Function via Selective Sampling COLT 2013 Fastfood - Computing Hilbert Space Expansions in loglinear time ICML 2013 Multiscale Dictionary Learning for Estimating Conditional Distributions NeurIPS 2013 Stochastic blockmodel approximation of a graphon: Theory and consistent estimation NeurIPS 2013 Density-Difference Estimation NeurIPS 2012 Locating Changes in Highly Dependent Data with Unknown Number of Change Points NeurIPS 2012 Minimax Manifold Estimation JMLR 2012 Nonparametric Estimation of Conditional Information and Divergences AISTATS 2012 Plug-in Approach to Active Learning JMLR 2012 Projection Retrieval for Classification NeurIPS 2012