| An Introduction to Matrix Concentration Inequalities Contributor(s): Tropp, Joel a. (Author) |
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ISBN: 1601988389 ISBN-13: 9781601988386 Publisher: Now Publishers OUR PRICE: $94.05 Product Type: Paperback Published: May 2015 |
| Additional Information |
| BISAC Categories: - Mathematics | Algebra - Elementary - Computers | Computer Science - Computers | Machine Theory |
| Dewey: 512.943 |
| Series: Foundations and Trends in Machine Learning |
| Physical Information: 0.53" H x 6.14" W x 9.21" (0.79 lbs) 252 pages |
| Descriptions, Reviews, Etc. |
| Publisher Description: 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. |