- Dianne O’Leary, The University of Maryland, College Park
Matrix approximation is a well-studied area of mathematics, but despite the attention it has received, many open questions remain involving existence, uniqueness, extensions to tensors, and efficient computation. The focus in this talk is on matrix approximation problems constrained in rank, sparsity, and nonnegativity, including a novel approach to uncertainty in matrix entries. Applications to deblurring pictures (images) and to document classification will be discussed.
About the Speaker:
Dianne Prost O'Leary is a Distinguished University Professor, emerita, at the University of Maryland, who held appointments in the university's Computer Science Department, Institute for Advanced Computer Studies (UMIACS), and Applied Mathematics & Statistics and Scientific Computing Program. Her research is in computational linear algebra and optimization, with applications including solution of ill-posed problems, image deblurring, information retrieval, and quantum computing.
About the Seminar Series:
The Householder Seminar series honors Dr. Alton S. Householder, who spent most of his career in the ORNL Mathematics Division (now the Computational Science and Mathematics Division. The series is sponsored jointly by the Computational and Applied Mathematics Group at Oak Ridge National Laboratory and the Department of Mathematics at the University of Tennessee, Knoxville. Its purpose is to have distinguished scientists present their research on various topics in computational and applied mathematics.
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