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Empirical Bayes (EB) is a popular framework for large-scale inference that aims to find data-driven estimators to compete with the Bayesian oracle that knows the true prior.
Asymptotically subminimax solutions of compound statistical decision problems
Herbert Robbins · 1951
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The population frequencies of species and the estimation of population parameters
I. J. Good · 1953
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Estimation by the minimum distance method
J. Wolfowitz · 1953
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Consistency of the maximum likelihood estimator in the presence of infinitely many incidental parameters
J. Kiefer and J. Wolfowitz · 1956
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An empirical Bayes approach to statistics
Herbert Robbins · 1956
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On the smooth empirical Bayes approach to testing of hypotheses and the compound decision problem
J. S. Maritz · 1968
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Orthogonal polynomials
Gábor Szeg˝o · 1975
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Maximum likelihood estimation of a compound poisson process
Léopold Simar · 1976
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Empirical Bayes estimation in Lebesgue-exponential families with rates near the best possible rate
R. S. Singh · 1979
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Mixtures of exponential distributions
Nicholas P. Jewell · 1982
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Parametric empirical Bayes inference: theory and applications
Carl N. Morris · 1983
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Monotone empirical Bayes estimators for the continuous one-parameter exponential family
J. C. van Houwelingen and Th. Stijnen · 1983
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A method for minimizing the impact of distributional assumptions in econometric models for duration data
J. Heckman and B. Singer · 1984
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Asymptotic properties of maximum likelihood estimates in the mixed Poisson model
Diane Lambert and Luke Tierney · 1984
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An introduction to empirical Bayes data analysis
George Casella · 1985
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Consistency of maximum likelihood estimators for certain nonparametric families, in particular: mixtures
J. Pfanzagl · 1988
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Empirical Bayes methods
J. S. Maritz and T. Lwin · 1989
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Hellinger-consistency of certain nonparametric maximum likelihood estimators
Sara van de Geer · 1993
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Convergence rate of sieve estimates
Xiaotong Shen and Wing Hung Wong · 1994
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Mixture models: theory, geometry, and applications
Bruce G Lindsay · 1995
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Probability inequalities for likelihood ratios and convergence rates of sieve MLEs
Wing Hung Wong and Xiaotong Shen · 1995
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Rates of convergence for the maximum likelihood estimator in mixture models
Sara van de Geer · 1996
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Weak Convergence and Empirical Processes
Aad van der Vaart and Jon A. Wellner · 1996
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Empirical bayes and compound estimation of normal means
Cun-Hui Zhang · 1997
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Nonparametric empirical Bayes estimation via wavelets
Marianna Pensky · 1999
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Rates of convergence for the Gaussian mixture sieve
Christopher R. Genovese and Larry Wasserman · 2000
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Entropies and rates of convergence for maximum likelihood and Bayes estimation for mixtures of normal densities
Subhashis Ghosal and Aad W. van der Vaart · 2001
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Compound decision theory and empirical Bayes methods
Cun-Hui Zhang · 2003
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Near-optimal-sample estimators for spherical gaussian mixtures
Ananda Theertha Suresh, Alon Orlitsky, Jayadev Acharya, and Ashkan Jafarpour · 2014
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Convergence rates of parameter estimation for some weakly identifiable finite mixtures
Nhat Ho and XuanLong Nguyen · 2016
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Consistency of the MLE under mixture models
Jiahua Chen · 2017
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Robust and proper learning for mixtures of gaussians via systems of polynomial inequalities
Jerry Li and Ludwig Schmidt · 2017
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Local moment matching: A unified methodology for symmetric functional estimation and distribution estimation under wasserstein distance
Yanjun Han, Jiantao Jiao, and Tsachy Weissman · 2018
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Strong identifiability and optimal minimax rates for finite mixture estimation
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Convergence rates of empirical Bayes estimation in exponential family
Jianjun Li, Shanti S. Gupta, and Friedrich Liese · 2005
Cited alongside, same era.
General empirical Bayes wavelet methods and exactly adaptive minimax estimation
Cun-Hui Zhang · 2005
Cited alongside, same era.
Posterior convergence rates of Dirichlet mixtures at smooth densities
Subhashis Ghosal and Aad van der Vaart · 2007
Cited alongside, same era.
Nonparametric empirical Bayes and compound decision approaches to estimation of a high-dimensional vector of normal means
Lawrence D. Brown and Eitan Greenshtein · 2009
Cited alongside, same era.
Bayesian methods for data analysis
Bradley P. Carlin and Thomas A. Louis · 2009
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Asymptotic efficiency of simple decisions for the compound decision problem
Eitan Greenshtein and Ya’acov Ritov · 2009
Cited alongside, same era.
Philippe Heinrich and Jonas Kahn · 2018
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Bayes, oracle Bayes and empirical Bayes
Bradley Efron · 2019
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Dualizing le cam’s method for functional estimation, with applications to estimating the unseens
Yury Polyanskiy and Yihong Wu · 2019
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Self-regularizing property of nonparametric maximum likelihood estimator in mixture models
Yury Polyanskiy and Yihong Wu · 2020
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On the nonparametric maximum likelihood estimator for gaussian location mixture densities with application to gaussian denoising
Sujayam Saha and Adityanand Guntuboyina · 2020
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Optimal estimation of Gaussian mixtures via denoised method of moments
Yihong Wu and Pengkun Yang · 2020
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Polynomial methods in statistical inference: Theory and practice
Yihong Wu and Pengkun Yang · 2020
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Computer age statistical inference—algorithms, evidence, and data science
Bradley Efron and Trevor Hastie · 2021
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Sharp regret bounds for empirical bayes and compound decision problems
Yury Polyanskiy and Yihong Wu · 2021
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A nonparametric regression approach to asymptotically optimal estimation of normal means
Alton Barbehenn and Sihai Dave Zhao · 2022
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Optimal empirical Bayes estimation for the Poisson model via minimum-distance methods
Soham Jana, Yury Polyanskiy, and Yihong Wu · 2022
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Minimax bounds for estimating multivariate Gaussian location mixtures
Arlene K. H. Kim and Adityanand Guntuboyina · 2022
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Poisson mean vector estimation with nonparametric maximum likelihood estimation and application to protein domain data
Hoyoung Park and Junyong Park · 2022
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Optimal estimation of high-dimensional Gaussian location mixtures
Natalie Doss, Yihong Wu, Pengkun Yang, and Harrison H. Zhou · 2023
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Empirical bayes via erm and rademacher complexities: the poisson model
Soham Jana, Yury Polyanskiy, Anzo Z Teh, and Yihong Wu · 2023
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Empirical bayes: Concepts and methods
Bradley Efron · 2024
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