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An Introduction to Matrix Concentration Inequalities (Foundations and Trends (R) in Machine Learning): 25 (Foundations and Trends® in Machine Learning) - Softcover
Synopsis
Random matrices now play a role in many areas of theoretical, applied, and computational mathematics. It is therefore desirable to have tools for studying random matrices that are flexible, easy to use, and powerful. Over the last fifteen years, researchers have developed a remarkable family of results, called matrix concentration inequalities, that achieve all of these goals. This monograph offers an invitation to the field of matrix concentration inequalities. It begins with some history of random matrix theory; it describes a flexible model for random matrices that is suitable for many problems; and it discusses the most important matrix concentration results. To demonstrate the value of these techniques, the presentation includes examples drawn from statistics, machine learning, optimization, combinatorics, algorithms, scientific computing, and beyond.
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- Publishernow publishers Inc
- Publication date2015
- ISBN 10 1601988389
- ISBN 13 9781601988386
- BindingPaperback
- LanguageEnglish
- Number of pages252
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An Introduction to Matrix Concentration Inequalities
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ISBN 10: 1601988389
ISBN 13: 9781601988386
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