arXiv stat.ML
· Papers
Optimal Top-$k$ Identification from Pairwise Comparisons
arXiv:2607.08979v1 Announce Type: cross Abstract: We study the active learning problem of fixed-confidence top-$k$ identification from noisy pairwise comparisons. In this problem, an algorithm sequentially chooses pairs of items to compare, observes the outcomes, and stops when it can return the set of top-$k$ items wi