[Statlist] ETH Young Data Science Researcher Seminar Zurich, Virtual Seminar by Yiqun Chen, University of Washington, 14.04.2022

[Kaiser-Heinzmann Susanne]

We are glad to announce the following talk in the virtual ETH Young Data Science Researcher Seminar Zurich

"Selective inference for k-means clustering“  
by Yiqun Chen, University of Washington

Time: Thursday, 14 April 2022, 16.00 - 17.00
Place: Zoom at https://ethz.zoom.us/j/62895316484

Abstract: We consider the problem of testing for a difference in means between clusters of observations identified via k-means clustering. In this setting, classical hypothesis tests lead to an inflated Type I error rate, because the clusters were obtained on the same data used for testing. To overcome this problem, we take a selective inference approach. We propose a finite-sample p-value that controls the selective Type I error for testing the difference in means between a pair of clusters obtained using k-means clustering, and show that it can be efficiently computed. We apply our proposal in simulation, and on hand-written digits data and single-cell RNA-sequencing data. This is joint work with Daniela Witten.

M. Azadkia, G. Chinot, J. Hörrmann, M. Löffler, A. Taeb, N. Zhivotovskiy


Seminar website: https://math.ethz.ch/sfs/news-and-events/young-data-science.html

Young Data Science Researcher Seminar Zurich – Seminar for Statistics | ETH Zurich
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