Active Learning for Top-K Rank Aggregation from Noisy Comparisons

Soheil Mohajer, Changho Suh, Adel Elmahdy

Abstract: We explore an active top-$K$ ranking problem based on pairwise comparisons that are collected possibly in a sequential manner as per our design choice. We consider two settings: (1) <em>top-$K$ sor...