143 citations · 179 across the 11 of their papers we have counts for
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cs.LG2022
Efficient computation of the Knowledge Gradient for Bayesian Optimization
Juan Ungredda, Michael Pearce, Juergen Branke
Bayesian optimization is a powerful collection of methods for optimizing stochastic expensive black box functions. One key component of a Bayesian optimization algorithm is the acq…
math.ST2022★ 2 cited
On the validity of bootstrap uncertainty estimates in the Mallows-Binomial model
Michael Pearce, Elena A. Erosheva
The Mallows-Binomial distribution is the first joint statistical model for rankings and ratings (Pearce and Erosheva, 2022). Because frequentist estimation of the model parameters…
stat.ME2022★ 6 cited
A Unified Statistical Learning Model for Rankings and Scores with Application to Grant Panel Review
Michael Pearce, Elena A. Erosheva
Rankings and scores are two common data types used by judges to express preferences and/or perceptions of quality in a collection of objects. Numerous models exist to study data of…