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Large-scale randomized experiments, sometimes called A/B tests, are increasingly prevalent in many industries.
An approximate distribution of estimates of variance components
Franklin E Satterthwaite · 1946
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The generalization of ‘student’s’ problem when several different population variances are involved
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An empirical Bayes approach to statistics
Herbert Robbins · 1956
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Inadmissibility of the usual estimator for the mean of a multivariate normal distribution
Charles Stein · 1956
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The empirical Bayes approach to statistical decision problems
Herbert Robbins · 1964
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Principles of Mathematical Analysis
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Stein’s paradox in statistics
Bradley Efron and Carl Morris · 1977
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Prediction and estimation for the compound Poisson distribution
Herbert Robbins · 1977
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Nonparametric maximum likelihood estimation of a mixing distribution
Nan Laird · 1978
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Probability density estimation using delta sequences
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On improving convergence rates for nonnegative kernel density estimators
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Abstract Inference
Ulf Grenander · 1981
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On trigonometric series estimates of densities
Peter Hall · 1981
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G. G. Walter · 1981
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Some thoughts on empirical Bayes estimation
Herbert Robbins · 1983
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Some data-analytic modifications to bayes-stein estimation
Tom Leonard · 1984
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On improving density estimators which are not bona fide functions
Leslaw Gajek · 1986
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Peter Hall · 1986
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The contributions of Herbert Robbins to mathematical statistics
Tze Leung Lai and David Siegmund · 1986
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Optimal rates of convergence for deconvolving a density
Raymond J Carroll and Peter Hall · 1988
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Deconvoluting kernel density estimators
Leonard Stefanski and Raymond J. Carroll · 1990
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Bayes empirical Bayes estimation for natural exponential families with quadratic variance functions
G. G. Walter and G. G. Hamedani · 1991
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Deconvolving compactly supported densities
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Aurore Delaigle and Alexander Meister · 2008
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Efficient projections onto the l 1 l_{1} -ball for learning in high dimensions
John Duchi, Shai Shalev-Shwartz, Yoram Singer, and Tushar Chandra · 2008
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A fast iterative shrinkage-thresholding algorithm for linear inverse problems
Amir Beck and Marc Teboulle · 2009
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Kernel density estimation via diffusion
Zdravko I Botev, Joseph F Grotowski, and Dirk P Kroese · 2010
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Extreme deconvolution: Inferring complete distribution functions from noisy, heterogeneous and incomplete observations
Jo Bovy, David W Hogg, and Sam T Roweis · 2011
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Bradley Efron and Robert Tibshirani · 1996
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On methods of sieves and penalization
Xiaotong Shen · 1997
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Partial Differential Equations
Lawrence C Evans · 1998
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Scale space view of curve estimation
Probal Chaudhuri and James Steven Marron · 2000
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Asymptotic Statistics
Aad W van der Vaart · 2000
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Trigonometric Series , volume I, II
Antoni Zygmund · 2002
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A spectral method for deconvolving a density
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Tweedie’s formula and selection bias
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Weiran Wang and Miguel Á. Carreira-Perpiñán · 2013
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Two modeling strategies for empirical Bayes estimation
Bradley Efron · 2014
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A geometric approach to density estimation with additive noise
Stefan Wager · 2014
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Objective Bayesian two sample hypothesis testing for online controlled experiments
Alex Deng · 2015
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Autograd: Effortless gradients in numpy
Dougal Maclaurin, David Duvenaud, and Ryan P Adams · 2015
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Adaptive restart for accelerated gradient schemes
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A decision theoretic approach to A/B testing
David Goldberg and James E Johndrow · 2017
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Singularity, misspecification, and the convergence rate of EM
Raaz Dwivedi, Nhat Ho, Koulik Khamaru, Michael I Jordan, Martin J Wainwright, and Bin Yu · 2018
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Scientists rise up against statistical significance
Valentin Amrhein, Sander Greenland, and Blake McShane · 2019
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A/B testing with fat tails
Eduardo M Azevedo, Deng Alex, Jose Montiel Olea, Justin M Rao, and E. Glen Weyl · 2019
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