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Sketching As A Tool For Numerical Linear Algebra
I will discuss how sketching techniques from the data stream literature can be used to speed up well-studied algorithms for problems occurring in numerical linear algebra, such as least squares regression and approximate singular value decomposition. I will also discuss how they can be used to achieve very efficient algorithms for variants of these problems, such as robust regression.
David Woodruff joined the algorithms and complexity group at IBM Almaden in 2007 after completing his Ph.D. at MIT in theoretical computer science. His interests are in compressed sensing, communication, numerical linear algebra, sketching, and streaming.