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Non-asymptotic Theory of Random Matrices: Extreme Singular Values
Open accessAbstract
The classical random matrix theory is mostly focused on asymptotic spectral properties of random matrices as their dimensions grow to infinity. At the same time many recent applications from convex geometry to functional analysis to information theory operate with random matrices in fixed dimensions. This survey addresses the non-asymptotic theory of extreme singular values of random matrices with independent entries. We focus on recently developed geometric methods for estimating the hard edge of random matrices (the smallest singular value).
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Metadata
- Authors
- Rudelson, M., & Vershynin, R.
- Venue
- Proceedings of the International Congress of Mathematicians 2010 (ICM 2010)
- Publisher
- Published by Hindustan Book Agency (HBA), India. WSPC Distribute for All Markets Except in India
- Published
- 2011-06
- Pages
- 1576-1602
- OpenAlex
- W2125319092
- Cited by
- 296
- References
- 1
- FWCI
- 57.90
- Type
- conference paper
- Language
- en
- Open access
- green
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- Rudelson, M., & Vershynin, R. (2011). Non-asymptotic Theory of Random Matrices: Extreme Singular Values. Proceedings of the International Congress of Mathematicians 2010 (ICM 2010). https://doi.org/10.1142/9789814324359_0111
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