10 citations · 11 across the 5 of their papers we have counts for
5 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 is the central objective of ranking and selection (R&S) and best arm identification (BAI). Traditional R&S or BAI approaches have p…
Sequential Additivity in Distributionally Robust Ranking and Selection
Zaile Li, Yuchen Wan, L. Jeff Hong
Ranking and selection (R&S) seeks to identify the alternative with the best mean performance from a finite collection of simulated alternatives. Its practical value depends on accu…
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…
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…
The (Surprising) Sample Optimality of Greedy Procedures for Large-Scale Ranking and Selection
Zaile Li, Weiwei Fan, L. Jeff Hong
Ranking and selection (R&S) aims to select the best alternative with the largest mean performance from a finite set of alternatives. Recently, considerable attention has turned tow…