The Higher Order Generalized Singular Value Decomposition

Charles Van Loan
Thu, Aug 8, 2013 to Sat, Aug 10, 2013
PIMS, University of British Columbia
Workshop on Numerical Linear Algebra and Optimization

Suppose you have a collection of data matrices each of which has the same number of columns. The HO-GSVD can be used to identify common features that are implicit across the collection. It works by identifying a certain (approximate) invariant subspace of a matrix that is a challenging combination of the collection matrices. In describing the computational process I will talk about the Higher Order
CS decomposition and a really weird optimization problem that I bet you have never seen before! Joint work with Orly Alter, Priya Ponnapalli, and Mike Saunders.