Approximate Ranking from Pairwise Comparisons

AISTATS, pp. 1057-1066, 2018.

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Abstract:

A common problem in machine learning is to rank a set of n items based on pairwise comparisons. Here ranking refers to partitioning the items into sets of pre-specified sizes according to their scores, which includes identification of the top-k items as the most prominent special case. The score of a given item is defined as the probabili...More

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