On Learning Mixture Models for Permutations
Flavio Chierichetti, Anirban Dasgupta, Ravi Kumar, Silvio Lattanzi · 2015
In this paper we consider the problem of learning a mixture of permutations, where each component of the mixture is generated by a stochastic process. Learning permutation mixtures arises in practical settings when a set of items is ranked by different sub-populations and the rankings of users in a sub-population tend to agree with each other. While there is some applied work on learning such mixtures, they have been mostly heuristic in nature.