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Cheng MAO (MIT) – "Breaking the n^{-1/2} barrier for permutation-based ranking models "

April 6, 2018 @ 2:00 pm - 3:15 pm
The Statistical Seminar: Every Monday at 2:00 pm.
Time: 2:00 pm – 3:15 pm
Date: 6th of April 2018 exceptionally on friday
Place: Room 3001.
Cheng MAO (MIT) “Breaking the n^{-1/2} barrier for permutation-based ranking models

Abstract:

The task of ranking from pairwise comparison data arises frequently in various applications, such as recommender systems, sports tournaments and social choice theory. There has been a recent surge of interest in studying permutation-based models, such as the noisy sorting model and the strong stochastic transitivity model, for ranking from pairwise comparisons. Although permutation-based ranking models are richer than traditional parametric models, a wide gap exists between the statistically optimal rate n^{-1} and the rate n^{-1/2} achieved by the state-of-the-art computationally efficient algorithms. In this talk, I will discuss new algorithms that achieve rates n^{-1} and n^{-3/4} for the noisy sorting model and the more general strong stochastic transitivity model respectively.
The talk is based on joint works with Jonathan Weed, Philippe Rigollet, Ashwin Pananjady and Martin J. Wainwright.
Organizers:
Cristina BUTUCEA, Alexandre TSYBAKOV, Eric MOULINES, Mathieu ROSENBAUM
Sponsors:
CREST-CMAP