[Statlist] Fwd: Next talk: Friday, 14.09.2018, with Armeen Taeb, Electrical Engineering California Institute of Technology

[Maurer Letizia]

Dear all,


Please note, we will have a coffee break from 16.00 - 16.30 in room HG G 14.1 and afterwards is the talk of Armeen Taeb!

Best regards

E-mail from the  Statlist at stat.ch<mailto:Statlist at stat.ch>  mailing list
_______________________________________________
ETH and University of Zurich

Organisers:

Proff. P. Bühlmann - L. Held - T. Hothorn - M. Maathuis -
N. Meinshausen - S. van de Geer - M. Wolf

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We are glad to announce the following talk:

Friday, 14.09.2018, at 16.30 h  ETH Zurich HG G19.1
with Armeen Taeb, Electrical Engineering California Institute of Technology

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Title:

False Discovery and Its Control For Low Rank Matrices <https://www.math.ethz.ch/sfs/news-and-events/research-seminar.html?s=hs18#e_12358>

Abstract:

Models specified by low-rank matrices are ubiquitous in contemporary applications. In many of these problem domains, the row/column space structure of a low-rank matrix carries information about some underlying phenomenon, and it is of interest in inferential settings to evaluate the extent to which the row/column spaces of an estimated low-rank matrix signify discoveries about the phenomenon. However, in contrast to variable selection, we lack a formal framework to assess true/false discoveries in low-rank estimation; in particular, the key source of difficulty is that the standard notion of a discovery is a discrete one that is ill-suited to the smooth structure underlying low-rank matrices. We address this challenge via a \emph{geometric} reformulation of the concept of a discovery, which then enables a natural definition in the low-rank case. We describe and analyze a generalization of the Stability Selection method of Meinshausen and B\"uhlmann to control for false discoveries in low-rank estimation, and we demonstrate its utility compared to previous approaches via numerical experiments.

This abstract is also to be found under the following link: http://stat.ethz.ch/events/research_seminar

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ETH Zürich
Letizia Maurer
Administration
Seminar für Statistik
HG G 10.3
Rämistrasse 101
8092 Zürich

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