The July 2016 summer session f the Park City Mathematics Institute, in Princeton, New Jersey, focused on the mathematics of data, an area of applied mathematics. The underlying ideas are that all data must be modeled--by a matrix, say, or a graph or a flat table--and to perform similar operations on very different types of data, there must be some sort of common mathematical structure--perhaps from linear algebra, graph theory, or logic. The lectures cover randomized numerical linear algebra, optimization algorithms for data analysis, introductory stochastic optimization, randomized methods for matrix computations, probabilistic methods for data science, and homological algebra and data. Annotation ©2019 Ringgold, Inc., Portland, OR (protoview.com)
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Michael W. Mahoney, University of California, Berkeley, CA.
John C. Duchi, Stanford University, CA.
Anna C. Gilbert, University of Michigan, Ann Arbor, MI.
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