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Gábor Lugosi coauthored concentration inequalities for self-bounding functions with Stéphane Boucheron and Pascal Massart. Their analysis uses the entropy method (probability) and a refined Herbst argument. Small coordinatewise changes can therefore yield strong control of a function's fluctuations even when it depends on many independent inputs.^[ref]

By Stéphane Boucheron, Gábor Lugosi, Pascal Massart.

Electronic Journal of Probability 14, paper 64, 1884–1899. DOI: doi.org/10.1214/EJP.v14-690 . Definitions 1–3 and Theorem 1, especially the additional increment hypothesis in the third conclusion, printed p. 1887. The primary PDF contains a typographical Pacal in its byline; the established Pascal spelling also appears in its correspondence address and publisher book byline.

Stéphane Boucheron contributed, with Gábor Lugosi and Pascal Massart, to the concentration theory of self-bounding functions. Their paper turns coordinatewise increment bounds into exponential tail bounds through the entropy method (probability). This supplies a reusable route from a function's local sensitivity to global concentration of measure.^[ref]