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Poster
Selective inference for group-sparse linear models
Fan Yang · Rina Barber · Prateek Jain · John Lafferty

Wed Dec 07 09:00 AM -- 12:30 PM (PST) @ Area 5+6+7+8 #165
in Wednesday Posters »

We develop tools for selective inference in the setting of group sparsity, including the construction of confidence intervals and p-values for testing selected groups of variables. Our main technical result gives the precise distribution of the magnitude of the projection of the data onto a given subspace, and enables us to develop inference procedures for a broad class of group-sparse selection methods, including the group lasso, iterative hard thresholding, and forward stepwise regression. We give numerical results to illustrate these tools on simulated data and on health record data.

Keywords: Sparsity and Feature Selection
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Author Information

Fan Yang (University of Chicago)
Rina Barber (University of Chicago)
Prateek Jain (Microsoft Research)
John Lafferty (Yale University)

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