A Linear Programming Inequality with Applications to Concentration of Measure

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dc.creatorKontorovich, Leonid
dc.date2006-10-24
dc.date.accessioned2026-07-07T07:29:22Z
dc.date.available2026-07-07T07:29:22Z
dc.descriptionWe prove an elementary yet useful inequality bounding the maximal value of certain linear programs. This leads directly to a bound on the martingale difference for arbitrarily dependent random variables, providing a generalization of some recent concentration of measure results. The linear programming inequality may be of independent interest.
dc.description9 pages
dc.identifierhttps://arxiv.org/abs/math/0610712
dc.identifierhttp://arxiv.org/abs/math/0610712
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/118081
dc.subjectFunctional Analysis
dc.subjectProbability
dc.subject90C05; 60A99; 46B20
dc.titleA Linear Programming Inequality with Applications to Concentration of Measure
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