ICML 2017Poster
Active Learning for Top-$K$ Rank Aggregation from Noisy Comparisons
Authors: 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)