John A. Hoffnagle, William D. Hinsberg, et al.
Microlithography 2003
We present a fast algorithm for approximate canonical correlation analysis (CCA). Given a pair of tall-and-thin matrices, the proposed algorithm first employs a randomized dimensionality reduction transform to reduce the size of the input matrices, and then applies any CCA algorithm to the new pair of matrices. The algorithm computes an approximate CCA to the original pair of matrices with provable guarantees while requiring asymptotically fewer operations than the state-of-the-art exact algorithms.
John A. Hoffnagle, William D. Hinsberg, et al.
Microlithography 2003
Satoshi Hada
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Charles Micchelli
Journal of Approximation Theory
R.B. Morris, Y. Tsuji, et al.
International Journal for Numerical Methods in Engineering