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Activity Number: 20
Type: Topic Contributed
Date/Time: Sunday, July 31, 2016 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistical Learning and Data Science
Abstract #321349 View Presentation
Title: A Multiparameter Mallows Model for Infinite Rankings
Author(s): Marina Meila*
Companies: University of Washington
Keywords: permutations ; partial ordering ; Mallows model ; distance based ranking model ; exponential family ; branch-and-bound

We study the natural extension of stagewise ranking to the the case of countably many items. We introduce the infinite version of the generalized Mallows model of (Fligner and Verducci, 1986), give procedures to estimate its parameters and central permutation from data, and demonstrate that it has sufficient statistics, being thus an exponential family model with continuous and discrete parameters. The experiments demonstrate that the Infinite Mallows Model can be tractably and usefully applied to truncated rankins of very large sets of items.

Joint work with Le Bao.

Authors who are presenting talks have a * after their name.

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