42 citations · 57 across the 7 of their papers we have counts for
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cs.LG2020
Exploiting Transitivity for Top-k Selection with Score-Based Dueling Bandits
Matthew Groves, Juergen Branke
We consider the problem of top-k subset selection in Dueling Bandit problems with score information. Real-world pairwise ranking problems often exhibit a high degree of transitivit…
cs.LG2020★ 4 cited
Bayesian Optimisation vs. Input Uncertainty Reduction
Juan Ungredda, Michael Pearce, Juergen Branke
Simulators often require calibration inputs estimated from real world data and the quality of the estimate can significantly affect simulation output. Particularly when performing…
math.OC2020★ 6 cited
BOP-Elites, a Bayesian Optimisation algorithm for Quality-Diversity search
Paul Kent, Juergen Branke
Quality Diversity (QD) algorithms such as MAP-Elites are a class of optimisation techniques that attempt to find a set of high-performing points from an objective function while en…