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Randomized Algorithms for Matrices and Data (Foundations and Trends(r) in Machine Learning)

Michael W. Mahoney




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 | #6138705 in Books |  Now Publishers Inc |  2011-11-16 | Original language:English | PDF # 1 |  9.21 x.24 x6.14l,.38 | File type: PDF | 114 pages

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Randomized algorithms for very large matrix problems have received a great deal of attention in recent years. Much of this work was motivated by problems in large-scale data analysis, largely since matrices are popular structures with which to model data drawn from a wide range of application domains, and the success of this line of work opens the possibility of performing matrix-based computations with truly massive data sets. Originating within theoretical computer sci...

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