6 citations · 18 across the 7 of their papers we have counts for
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stat.ML2016★ 5 cited
Bayesian Optimization with Shape Constraints
Michael Jauch, Víctor Peña
In typical applications of Bayesian optimization, minimal assumptions are made about the objective function being optimized. This is true even when researchers have prior informati…
stat.ME2016★ 5 cited
Bayesian variable selection in high dimensional problems without assumptions on prior model probabilities
James O. Berger, Gonzalo Garcia-Donato, Miguel A. Martinez-Beneito +1
We consider the problem of variable selection in linear models when , the number of potential regressors, may exceed (and perhaps substantially) the sample size (which is po…