4 papers
UCB for Large-Scale Pure Exploration: Beyond Sub-Gaussianity
Zaile Li, Weiwei Fan, L. Jeff Hong
Selecting the best alternative from a finite set represents a broad class of pure exploration problems. Traditional approaches to pure exploration have predominantly relied on Gaus…
Additive Distributionally Robust Ranking and Selection
Zaile Li, Yuchen Wan, L. Jeff Hong
Ranking and selection (R&S) aims to identify the alternative with the best mean performance among simulated alternatives. The practical value of R&S depends on accurate simulat…
Efficient Budget Allocation for Large-Scale LLM-Enabled Virtual Screening
Zaile Li, Weiwei Fan, L. Jeff Hong
Screening tasks that aim to identify a small subset of top alternatives from a large pool are common in business decision-making processes. These tasks often require substantial hu…
New Additive OCBA Procedures for Robust Ranking and Selection
Yuchen Wan, Zaile Li, L. Jeff Hong
Robust ranking and selection (R&S) is an important and challenging variation of conventional R&S that seeks to select the best alternative among a finite set of alternatives. It ca…