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Schur-monotonic Semi-separable Approximations of Symmetric Positive Definite Matrices
Applied Math| Speaker: | Ming Gu, University of California, Berkeley |
| Location: | 1147 MSB |
| Start time: | Fri, Apr 28 2006, 4:10PM |
Description
Abstract: For a given symmetric positive definite matrix A, we develop
a fast and backward stable algorithm to approximate A by a symmetric
semi-separable matrix, accurate to any prescribed tolerance. In
addition, our algorithm guarantees the positive-definiteness of the
semi-separable matrix by embedding an approximation strategy inside the
Cholesky factorization procedure to ensure that each Schur complement
during the Cholesky factorization is more positive definite after
approximation. We will present experimental numerical results and
discuss potential implications of this work.
Joint work with S. Chandrasekaran of UCSB, X. S. Li of LBNL and P. S. Vassilevski of LLNB.