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We introduce a new empirical Bayes approach for large-scale multiple linear regression.
On information and sufficiency
S. Kullback and R. A. Leibler · 1951
Earlier work this paper cites.
Solution of incorrectly formulated problems and the regularization method
A. N. Tikhonov · 1963
Earlier work this paper cites.
The empirical Bayes approach to statistical decision problems
H. Robbins · 1964
Earlier work this paper cites.
Maximum-likelihood estimation for the mixed analysis of variance model
H. O. Hartley and J. N. K. Rao · 1967
Earlier work this paper cites.
Ridge regression: biased estimation for nonorthogonal problems
A. E. Hoerl and R. W. Kennard · 1970
Earlier work this paper cites.
Stein’s estimation rule and its competitors—an empirical Bayes approach
B. Efron and C. Morris · 1973
Earlier work this paper cites.
Maximum likelihood from incomplete data via the EM algorithm
A. P. Dempster, N. M. Laird, and D. B. Rubin · 1977
Earlier work this paper cites.
Parametric empirical Bayes inference: theory and applications
C. N. Morris · 1983
Earlier work this paper cites.
Studies in the history of probability and statistics XL: Boscovich, Simpson and a 1760 manuscript note on fitting a linear relation
S. M. Stigler · 1984
Earlier work this paper cites.
Statistical Decision Theory and Bayesian Analysis
J. O. Berger · 1985
Earlier work this paper cites.
Bayes and empirical Bayes shrinkage estimation of regression coefficients
F. Nebebe and T. Stroud · 1986
Earlier work this paper cites.
Unimodality, convexity, and applications
S. Dharmadhikari and K. Joag-Dev · 1988
Earlier work this paper cites.
Bayesian variable selection in linear regression
T. J. Mitchell and J. J. Beauchamp · 1988
Earlier work this paper cites.
Generalized Linear Models , volume 37 of Monographs on Statistics and Applied Probability
P. McCullagh and J. A. Nelder · 1989
Earlier work this paper cites.
On the convergence of the coordinate descent method for convex differentiable minimization
Z. Q. Luo and P. Tseng · 1992
Earlier work this paper cites.
Variable selection via Gibbs sampling
E. I. George and R. E. McCulloch · 1993
Earlier work this paper cites.
Exploiting tractable substructures in intractable networks
L. K. Saul and M. I. Jordan · 1996
Earlier work this paper cites.
Regression shrinkage and selection via the lasso
R. Tibshirani · 1996
Earlier work this paper cites.
Approaches for Bayesian variable selection
E. I. George and R. E. McCulloch · 1997
Earlier work this paper cites.
Penalized regressions: The Bridge versus the Lasso
W. J. Fu · 1998
Earlier work this paper cites.
Nonlinear Programming
D. P. Bertsekas · 1999
Earlier work this paper cites.
An introduction to variational methods for graphical models
M. I. Jordan, Z. Ghahramani, T. S. Jaakkola, and L. K. Saul · 1999
Earlier work this paper cites.
Empirical Bayes: past, present and future
B. P. Carlin and T. A. Louis · 2000
Earlier work this paper cites.
Calibration and empirical Bayes variable selection
E. I. George and D. P. Foster · 2000
Earlier work this paper cites.
Variational learning for switching state-space models
Z. Ghahramani and G. E. Hinton · 2000
Earlier work this paper cites.
Bayesian parameter estimation via variational methods
T. S. Jaakkola and M. I. Jordan · 2000
Earlier work this paper cites.
Empirical Bayes Gibbs sampling
G. Casella · 2001
Earlier work this paper cites.
The practical implementation of Bayesian model selection
H. Chipman, E. I. George, and R. E. McCulloch · 2001
Earlier work this paper cites.
A variational method for learning sparse and overcomplete representations
M. Girolami · 2001
Earlier work this paper cites.
Prediction of total genetic value using genome-wide dense marker maps
T. H. Meuwissen, B. J. Hayes, and M. E. Goddard · 2001
Earlier work this paper cites.
Convergence of a block coordinate descent method for nondifferentiable minimization
P. Tseng · 2001
Earlier work this paper cites.
Subset Selection in Regression
A. J. Miller · 2002
Earlier work this paper cites.
Latent Dirichlet allocation
D. M. Blei, A. Y. Ng, and M. I. Jordan · 2003
Earlier work this paper cites.
Adaptive sparseness for supervised learning
M. A. T. Figueiredo · 2003
Earlier work this paper cites.
Needles and straw in haystacks: empirical Bayes estimates of possibly sparse sequences
I. M. Johnstone and B. W. Silverman · 2004
Earlier work this paper cites.
Linear models and empirical Bayes methods for assessing differential expression in microarray experiments
G. K. Smyth · 2004
Earlier work this paper cites.
Empirical Bayes selection of wavelet thresholds
I. M. Johnstone and B. W. Silverman · 2005
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Inadequacy of interval estimates corresponding to variational bayesian approximations
B. Wang and D. M. Titterington · 2005
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Efficient empirical Bayes variable selection and estimation in linear models
M. Yuan and Y. Lin · 2005
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Regularization and variable selection via the elastic net
H. Zou and T. Hastie · 2005
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Pattern Recognition and Machine Learning
C. Bishop · 2006
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Pathwise coordinate optimization
J. Friedman, T. Hastie, H. Höfling, and R. Tibshirani · 2007
Cited alongside, same era.
Proximal algorithms
N. Parikh and S. Boyd · 2014
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Genome-wide regression and prediction with the BGLR statistical package
P. Perez and G. de los Campos · 2014
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On variational Bayes estimation and variational information criteria for linear regression models
C. You, J. T. Ormerod, and S. Müller · 2014
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Dirichlet–Laplace priors for optimal shrinkage
N. S. P. Anirban Bhattacharya, Debdeep Pati and D. B. Dunson · 2015
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A gene-based association method for mapping traits using reference transcriptome data
E. R. Gamazon, H. E. Wheeler, K. P. Shah, S. V. Mozaffari, K. Aquino-Michaels, R. J. Carroll, A. E. Eyler, J. C. Denny, D. L. Nicolae, N. J. Cox, and H. K. Im · 2015
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Simultaneous discovery, estimation and prediction analysis of complex traits using a Bayesian mixture model
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Microarrays, empirical Bayes and the two-groups model
B. Efron · 2008
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Mixtures of g g priors for Bayesian variable selection
F. Liang, R. Paulo, G. Molina, M. a. Clyde, and J. O. Berger · 2008
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The Bayesian Lasso
T. Park and G. Casella · 2008
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Graphical models, exponential families, and variational inference
M. J. Wainwright and M. I. Jordan · 2008
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Coordinate descent algorithms for lasso penalized regression
T. T. Wu and K. Lange · 2008
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Bayesian lasso regression
C. Hans · 2009
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G. Moser, S. H. Lee, B. J. Hayes, M. E. Goddard, N. R. Wray, and P. M. Visscher · 2015
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Coordinate descent algorithms
S. J. Wright · 2015
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Variance adaptive shrinkage (vash): flexible empirical Bayes estimation of variances
M. Lu and M. Stephens · 2016
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False discovery rates: a new deal
M. Stephens · 2016
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The Trimmed Lasso: sparsity and robustness
D. Bertsimas, M. S. Copenhaver, and R. Mazumder · 2017
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Variational inference: a review for statisticians
D. M. Blei, A. Kucukelbir, and J. D. McAuliffe · 2017
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varbvs: fast variable selection for large-scale regression
P. Carbonetto, X. Zhou, and M. Stephens · 2017
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Genetic effects on gene expression across human tissues
GTEx Consortium · 2017
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Bayesian lasso: an extension for genome-wide association study
L. Joo · 2017
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False discoveries occur early on the lasso path
W. Su, M. Bogdan, and E. Candes · 2017
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Debiasing the lasso: optimal sample size for Gaussian designs
A. Javanmard and A. Montanari · 2018
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The Spike-and-Slab LASSO
V. Ročková and E. I. George · 2018
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Solving the empirical Bayes normal means problem with correlated noise
L. Sun and M. Stephens · 2018
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Signatures of negative selection in the genetic architecture of human complex traits
J. Zeng, R. de Vlaming, Y. Wu, M. R. Robinson, L. R. Lloyd-Jones, L. Yengo, C. X. Yap, A. Xue, J. Sidorenko, A. F. McRae, J. E. Powell, G. W. Montgomery, A. Metspalu, T. Esko, G. Gibson, N. R. Wray, P. M. Visscher, and J. Yang · 2018
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Lasso meets horseshoe: a survey
A. Bhadra, J. Datta, N. G. Polson, and B. Willard · 2019
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Bayes, oracle Bayes and empirical Bayes
B. Efron · 2019
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R: a language and environment for statistical computing
R Core Team · 2019
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Flexible statistical methods for estimating and testing effects in genomic studies with multiple conditions
S. M. Urbut, G. Wang, P. Carbonetto, and M. Stephens · 2019
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Learning from a lot: empirical Bayes for high-dimensional model-based prediction
M. A. van de Wiel, D. E. Te Beest, and M. M. Münch · 2019
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Trimming the ℓ 1 \ell_{1} regularizer: statistical analysis, optimization, and applications to deep learning
J. Yun, P. Zheng, E. Yang, A. Lozano, and A. Aravkin · 2019
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Heavy-tailed prior distributions for sequence count data: removing the noise and preserving large differences
A. Zhu, J. G. Ibrahim, and M. I. Love · 2019
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Empirical Bayes shrinkage and false discovery rate estimation, allowing for unwanted variation
D. Gerard and M. Stephens · 2020
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Fast best subset selection: coordinate descent and local combinatorial optimization algorithms
H. Hazimeh and R. Mazumder · 2020
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A fast algorithm for maximum likelihood estimation of mixture proportions using sequential quadratic programming
Y. Kim, P. Carbonetto, M. Stephens, and M. Anitescu · 2020
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A simple new approach to variable selection in regression, with application to genetic fine mapping
G. Wang, A. Sarkar, P. Carbonetto, and M. Stephens · 2020
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The Trimmed Lasso: sparse recovery guarantees and practical optimization by the generalized soft-min penalty
T. Amir, R. Basri, and B. Nadler · 2021
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Spike-and-slab meets LASSO: A review of the spike-and-slab LASSO
R. Bai, V. Ročková, and E. I. George · 2021
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Empirical Bayes matrix factorization
W. Wang and M. Stephens · 2021
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Flexible signal denoising via flexible empirical Bayes shrinkage
Z. Xing, P. Carbonetto, and M. Stephens · 2021
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Variational Bayes for high-dimensional linear regression with sparse priors
K. Ray and B. Szabó · 2022
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Fast and accurate Bayesian polygenic risk modeling with variational inference
S. Zabad, S. Gravel, and Y. Li · 2023
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