[Statlist] Next talk: Friday, November 8, 2013 with Fabian Wauthier, University of Oxford, 15.15h , HG G 19.1

[Cecilia Rey]

Please note that the time of the talk is as ususal on 15.15 in HG G 19.1.


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ETH and University of Zurich

Organisers:
Proff. P. Bühlmann - L. Held - T. Hothorn - H.R. Kuensch - M. Maathuis - 
N. Meinshausen - S. van de Geer - M. Wolf

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We are glad to announce the following talk

Friday, November 8, 2013, 15.15h  ETH Zurich HG G 19.1 
with Fabian Wauthier, University of Oxford, Department of Statistics 

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Title:
A Comparative Framework for Preconditioned Lasso Algorithms

Abstract:
The Lasso is a cornerstone of modern multivariate data analysis, yet its performance suffers in the common situation in which covariates are correlated. This limitation has led to a growing number of Preconditioned Lasso algorithms that pre-multiply X and y by matrices P_X, P_y prior to running the standard Lasso. A direct comparison of these and similar Lasso-style algorithms to the original Lasso is difficult because the performance of all of these methods depends critically on an auxiliary penalty parameter \lambda. In this paper we propose an agnostic, theoretical framework for comparing Preconditioned Lasso algorithms to the Lasso without having to choose \lambda. We apply our framework to three Preconditioned Lasso instances.

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