Introduction to the non-asymptotic analysis of random matrices

@inproceedings{Vershynin2012IntroductionTT,
  title={Introduction to the non-asymptotic analysis of random matrices},
  author={R. Vershynin},
  booktitle={Compressed Sensing},
  year={2012}
}
  • R. Vershynin
  • Published in Compressed Sensing 2012
  • Mathematics, Computer Science
This is a tutorial on some basic non-asymptotic methods and concepts in random matrix theory. The reader will learn several tools for the analysis of the extreme singular values of random matrices with independent rows or columns. Many of these methods sprung off from the development of geometric functional analysis since the 1970's. They have applications in several fields, most notably in theoretical computer science, statistics and signal processing. A few basic applications are covered in… Expand
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References

SHOWING 1-10 OF 137 REFERENCES
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