Nils Rudi

Optimal Top-$k$ Identification from Pairwise Comparisons

We study the active learning problem of fixed-confidence top-$k$ identification from noisy pairwise comparisons under latent-utility models. The objective is to identify the top-$k$ items with probability at least $1-\delta$ while using as few comparisons as possible by adaptively selecting which pa…