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Activity Number: 50
Type: Invited
Date/Time: Sunday, August 9, 2015 : 4:00 PM to 5:50 PM
Sponsor: Section on Statistical Learning and Data Mining
Abstract #314658
Title: Generalized Convex Banding for Covariance Estimation
Author(s): Jacob Bien*
Companies: Cornell University
Keywords: covariance ; high-dimensional ; convex

Reliably estimating the covariance matrix is notoriously difficult in high dimensions. Numerous regularized estimators have been developed that curb the curse of dimensionality by shrinking eigenvalues, seeking sparse entries, or using problem-specific information such as a known ordering of the variables. We consider a new class of estimators (of both covariance and inverse covariance matrices) that is in the spirit of this last sort of regularized estimator but which can be applied in a much wider set of situations.

Authors who are presenting talks have a * after their name.

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