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Gunnar Martinsson is an assistant professor of applied mathematics at the University of Colorado at Boulder. He graduated from Chalmers University of Technology in Gothenburg, Sweden, in 1998, and earned his PhD in 2002 from the Computational and Applied Mathematics program at the University of Texas at Austin. His research interests include numerical linear algebra, fast solvers for linear PDEs, and applied harmonic analysis. A particular focus of his research is the development of algorithms specifically designed for very large scale problems. Such problems require algorithms whose complexity scales linearly with problem size, that can efficiently exploit parallel processors in a variety of configurations, that can run with the data stored out-of-core or streamed, and that maintain optimal accuracy even for very large problems.
Making Very Large-Scale Linear Algebraic Computations Possible Via Randomization
as author at 23rd Annual Conference on Neural Information Processing Systems (NIPS), Vancouver 2009,