Empirical Bayes: Past, Present and Future

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Probabilistic Neural Architecture Search (2019, methodology): “Given a supervised task and denoting with y the targets and with X the input features, this is achieved by optimizing the continuous prior hyper-parameters π through an empirical Bayes Monte Carlo procedure (Carlin and Louis, 2000).”
Bayes and empirical-Bayes multiplicity adjustment in the variable-selection problem (2010, methodology): “(1998); for gene-expression studies, see Do, Muller and Tang (2005); for econo? metrics, see Ley and Steel (2009); for Gaussian graphical models, see Carvalho and Scott (2009); and for time-series data, see Scott (2009).”