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An Introduction to Matrix Concentration Inequalities

arXiv 1501.01571 ↗First posted 7 Jan 2015math.PR cs.DS cs.ITcited by 391

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Abstract (arXiv)

In recent years, random matrices have come to play a major role in computational mathematics, but most of the classical areas of random matrix theory remain the province of experts. Over the last decade, with the advent of matrix concentration inequalities, research has advanced to the point where we can conquer many (formerly) challenging problems with a page or two of arithmetic. The aim of this monograph is to describe the most successful methods from this area along with some interesting examples that these techniques can illuminate.

Key facts. Cited by 391 papers in the map (data through 7 Oct 2026). First posted on arXiv 7 Jan 2015.

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Citing papers per year: 2020: 2; 2021: 72; 2022: 59; 2023: 67; 2024: 53; 2025: 62; 2026: 76.

391 papers.

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