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(1974)
New York-Heidelberg
- Publisher
- Springer International Publishing
- Copyright
- © Springer International Publishing Switzerland 2016
- ISBN
- 978-3-319-40517-9
- Pages
- 173 –202
- DOI
- 10.1007/978-3-319-40519-3_8
- Publisher site
- See Chapter on Publisher Site
Abstract
[In contemporary applied and computational mathematics, a frequent challenge is to bound the expectation of the spectral norm of a sum of independent random matrices. This quantity is controlled by the norm of the expected square of the random matrix and the expectation of the maximum squared norm achieved by one of the summands; there is also a weak dependence on the dimension of the random matrix. The purpose of this paper is to give a complete, elementary proof of this important inequality.]
Published: Sep 22, 2016
Keywords: Probability inequality; Random matrix; Sum of independent random variables