Concentration Inequalities & Empirical Processes Reading List

Curated by Mouhssine Rifaki | Stanford Electrical Engineering | Last updated August 2026

High-probability guarantees underpin statistical learning. From Hoeffding's inequality to Talagrand's concentration and Rademacher complexities, these works give the tools to reason about samples with rigor.

Concentration Inequalities & Empirical Processes: 10 key papers

1. User-friendly tail bounds for sums of random matrices
   Tropp. arXiv 2010.
2. An Introduction to Matrix Concentration Inequalities
   Tropp. arXiv 2015.
3. Concentration of Measure Inequalities in Information Theory, Communications and Coding (Second Edition)
   Raginsky and Sason. arXiv 2012.
4. Tail bounds via generic chaining
   Dirksen. arXiv 2013.
5. A Short Note on Concentration Inequalities for Random Vectors with SubGaussian Norm
   Jin et al. arXiv 2019.
6. Bernstein type inequality for a class of dependent random matrices
   Banna et al. arXiv 2015.
7. Introduction to the non-asymptotic analysis of random matrices
   Vershynin. arXiv 2010.
8. Concentration inequalities for matrix martingales in continuous time
   Bacry et al. Probability Theory and Related Fields 2017.
9. Empirical Bernstein Bounds and Sample Variance Penalization
   Maurer and Pontil. arXiv 2009.
10. Time-uniform Chernoff bounds via nonnegative supermartingales
    Howard et al. arXiv 2018.

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