A Linear Programming Inequality with Applications to Concentration of Measure
Functional Analysis
2007-05-23 v1 Probability
Abstract
We 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.
Cite
@article{arxiv.math/0610712,
title = {A Linear Programming Inequality with Applications to Concentration of Measure},
author = {Leonid Kontorovich},
journal= {arXiv preprint arXiv:math/0610712},
year = {2007}
}
Comments
9 pages