Non-Parametric Inference Adaptive to Intrinsic Dimension
暂无分享,去创建一个
Khashayar Khosravi | Vasilis Syrgkanis | Greg Lewis | Vasilis Syrgkanis | Khashayar Khosravi | Greg Lewis
[1] Zhiwei Steven Wu,et al. Orthogonal Random Forest for Causal Inference , 2018, ICML.
[2] F. Wolak,et al. Structural Econometric Modeling: Rationales and Examples from Industrial Organization , 2004 .
[3] Sanjoy Dasgupta,et al. Which Spatial Partition Trees are Adaptive to Intrinsic Dimension? , 2009, UAI.
[4] Adam Krzyzak,et al. A Distribution-Free Theory of Nonparametric Regression , 2002, Springer series in statistics.
[5] Samory Kpotufe,et al. k-NN Regression Adapts to Local Intrinsic Dimension , 2011, NIPS.
[6] Zhiwei Steven Wu,et al. Orthogonal Random Forest for Heterogeneous Treatment Effect Estimation , 2018, ArXiv.
[7] Alexandr Andoni,et al. Optimal Hashing-based Time-Space Trade-offs for Approximate Near Neighbors , 2016, SODA.
[8] J. Tenenbaum,et al. A global geometric framework for nonlinear dimensionality reduction. , 2000, Science.
[9] Alessandro Rinaldo,et al. Uniform Convergence Rate of the Kernel Density Estimator Adaptive to Intrinsic Volume Dimension , 2018, ICML.
[10] Y. Mack,et al. Local Properties of k-NN Regression Estimates , 1981 .
[11] J. Robins,et al. Locally Robust Semiparametric Estimation , 2016, Econometrica.
[12] R. Samworth. Optimal weighted nearest neighbour classifiers , 2011, 1101.5783.
[13] Ilias Zadik,et al. Orthogonal Machine Learning: Power and Limitations , 2017, ICML.
[14] R. Tibshirani,et al. Local Likelihood Estimation , 1987 .
[15] Demian Pouzo,et al. Efficient Estimation of Semiparametric Conditional Moment Models with Possibly Nonsmooth Residuals , 2008 .
[16] Victor Chernozhukov,et al. Inference on Treatment Effects after Selection Amongst High-Dimensional Controls , 2011 .
[17] Alexandr Andoni,et al. Approximate Nearest Neighbor Search in High Dimensions , 2018, Proceedings of the International Congress of Mathematicians (ICM 2018).
[18] Jingbo Wang,et al. DNN: A Two-Scale Distributional Tale of Heterogeneous Treatment Effect Inference , 2018, ArXiv.
[19] Vasilis Syrgkanis,et al. Plug-in Regularized Estimation of High-Dimensional Parameters in Nonlinear Semiparametric Models , 2018, ArXiv.
[20] W. Newey,et al. Kernel Estimation of Partial Means and a General Variance Estimator , 1994, Econometric Theory.
[21] Vikas K. Garg,et al. Adaptivity to Local Smoothness and Dimension in Kernel Regression , 2013, NIPS.
[22] Sendhil Mullainathan,et al. Machine Learning: An Applied Econometric Approach , 2017, Journal of Economic Perspectives.
[23] Leo Breiman,et al. Random Forests , 2001, Machine Learning.
[24] Jianqing Fan,et al. Local maximum likelihood estimation and inference , 1998 .
[25] Heinrich Jiang. Rates of Uniform Consistency for k-NN Regression , 2017, ArXiv.
[26] J. Robins,et al. Double/Debiased Machine Learning for Treatment and Structural Parameters , 2017 .
[27] Lirong Xue,et al. Achieving the time of 1-NN, but the accuracy of k-NN , 2017, AISTATS.
[28] Vasilis Syrgkanis,et al. Regularized Orthogonal Machine Learning for Nonlinear Semiparametric Models , 2018 .
[29] B. Efron. The jackknife, the bootstrap, and other resampling plans , 1987 .
[30] A. Belloni,et al. Inference on Treatment Effects after Selection Amongst High-Dimensional Controls , 2011, 1201.0224.
[31] Susan Athey,et al. The State of Applied Econometrics - Causality and Policy Evaluation , 2016, 1607.00699.
[32] Abubakr Gafar Abdalla,et al. Probability Theory , 2017, Encyclopedia of GIS.
[33] C. J. Stone,et al. Optimal Global Rates of Convergence for Nonparametric Regression , 1982 .
[34] Thomas B. Berrett,et al. Efficient multivariate entropy estimation via $k$-nearest neighbour distances , 2016, The Annals of Statistics.
[35] Christian Hansen,et al. High-Dimensional Methods and Inference on Structural and Treatment Effects , 2013 .
[36] Mikhail Belkin,et al. Laplacian Eigenmaps for Dimensionality Reduction and Data Representation , 2003, Neural Computation.
[37] L. Hansen. Large Sample Properties of Generalized Method of Moments Estimators , 1982 .
[38] Julie Tibshirani,et al. Local Linear Forests , 2018, J. Comput. Graph. Stat..
[39] W. Newey,et al. Double machine learning for treatment and causal parameters , 2016 .
[40] W. Newey,et al. Constrained Conditional Moment Restriction Models , 2015, Econometrica.
[41] J. Robins,et al. Toward a curse of dimensionality appropriate (CODA) asymptotic theory for semi-parametric models. , 1997, Statistics in medicine.
[42] J. Lafferty,et al. Rodeo: Sparse, greedy nonparametric regression , 2008, 0803.1709.
[43] S. Athey,et al. Generalized random forests , 2016, The Annals of Statistics.
[44] Devavrat Shah,et al. Explaining the Success of Nearest Neighbor Methods in Prediction , 2018, Found. Trends Mach. Learn..
[45] Arthur Lewbel,et al. A local generalized method of moments estimator , 2007 .
[46] J. Staniswalis. The Kernel Estimate of a Regression Function in Likelihood-Based Models , 1989 .
[47] G. Imbens,et al. Approximate residual balancing: debiased inference of average treatment effects in high dimensions , 2016, 1604.07125.
[48] Luc Devroye,et al. Lectures on the Nearest Neighbor Method , 2015 .
[49] W. Newey,et al. 16 Efficient estimation of models with conditional moment restrictions , 1993 .
[50] Eric R. Ziegel,et al. The Elements of Statistical Learning , 2003, Technometrics.
[51] Susan Athey,et al. Recursive partitioning for heterogeneous causal effects , 2015, Proceedings of the National Academy of Sciences.
[52] J. Norris. Appendix: probability and measure , 1997 .
[53] Gérard Biau,et al. Analysis of a Random Forests Model , 2010, J. Mach. Learn. Res..
[54] Heinrich Jiang,et al. Non-Asymptotic Uniform Rates of Consistency for k-NN Regression , 2017, AAAI.
[55] Sanjoy Dasgupta,et al. Random projection trees and low dimensional manifolds , 2008, STOC.
[56] Sanjoy Dasgupta,et al. A tree-based regressor that adapts to intrinsic dimension , 2012, J. Comput. Syst. Sci..
[57] W. Hoeffding. Probability Inequalities for sums of Bounded Random Variables , 1963 .
[58] Stefan Wager,et al. Estimation and Inference of Heterogeneous Treatment Effects using Random Forests , 2015, Journal of the American Statistical Association.
[59] Liva Ralaivola,et al. Empirical Bernstein Inequalities for U-Statistics , 2010, NIPS.
[60] Xiaohong Chen,et al. Efficient Estimation of Models with Conditional Moment Restrictions Containing Unknown Functions , 2003 .
[61] P. Assouad. Plongements lipschitziens dans Rn , 2003 .
[62] S T Roweis,et al. Nonlinear dimensionality reduction by locally linear embedding. , 2000, Science.
[63] C. J. Stone,et al. Consistent Nonparametric Regression , 1977 .
[64] Jean-Philippe Vert,et al. Consistency of Random Forests , 2014, 1405.2881.
[65] C. D. Cutler,et al. A REVIEW OF THE THEORY AND ESTIMATION OF FRACTAL DIMENSION , 1993 .
[66] A. Belloni,et al. Program evaluation and causal inference with high-dimensional data , 2013, 1311.2645.