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University of Cambridge > Talks.cam > Applied and Computational Analysis > An Introduction to Randomized Algorithms for Matrix Computations
An Introduction to Randomized Algorithms for Matrix ComputationsAdd to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact ai10. This is a joint ACA–CCIMI seminar The emergence of massive data sets, over the past twenty or so years, has lead to the development of Randomized Numerical Linear Algebra. Fast and accurate randomized matrix algorithms are being designed for applications in machine learning, population genomics, astronomy, nuclear engineering, and optimal experimental design. We give a flavour of randomized algorithms for the solution of least squares/regression problems. Along the way we illustrate important concepts from numerical analysis (conditioning and pre-conditioning), probability (concentration inequalities), and statistics (sampling and leverage scores). This talk is part of the Applied and Computational Analysis series. This talk is included in these lists:
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