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Christophe GIRAUD (Université Paris-Sud) – “Partial recovery bounds for clustering with (corrected) relaxed Kmeans (2/2)”
October 1, 2:00 pm - 3:15 pm
The Statistical Seminar: Every Monday at 2:00 pm.
Time: 2:00 pm – 3:15 pm
Date: 1st of October 2018
Place: Room 3001.
Christophe GIRAUD (Université Paris-Sud) “Partial recovery bounds for clustering with (corrected) relaxed Kmeans (2/2)”
Abstract: We will explain why, in a clustering context, Kmeans must and can be debiased. We will then discuss how a convex relaxation of the corrected Kmeans can be applied in various setting (including mixture of sub-Gaussian distribution, SBM, Ising-Block model, etc) and we will provide some optimal exponential bounds in terms of partial recovery of the clusters. Hence, the relaxed (corrected) Kmeans appears to be a versatile clustering tool, with the nice feature to have a single tuning parameter (the number K of clusters).
Cristina BUTUCEA, Alexandre TSYBAKOV, Julie JOSSE, Eric MOULINES, Mathieu ROSENBAUM