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High-dimensional variable selection via sure independence screening

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If you have a question about this talk, please contact Shakir Mohamed.

I will discuss a simple but important new idea in high-dimensional variable selection, namely Sure Independence Screening. This was proposed in the context of the linear model by Fan and Lv (2008) in a JRSSB discussion paper, available at

http://www3.interscience.wiley.com/cgi-bin/fulltext/121429351/PDFSTART

I also hope to discuss a recent JMLR paper by Fan, Samworth and Wu (2009), where we aimed to extend the scope of these procedures to more general models, as well as looking at variants, designed for instance to reduce the false selection rate. The paper can be found at

http://jmlr.csail.mit.edu/papers/volume10/fan09a/fan09a.pdf

This talk is part of the Machine Learning Reading Group @ CUED series.

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