Concentration inequalities are fundamental tools in probabilistic combinatorics and theoretical computer science for proving that random functions are near their means. Of particular importance is the case where f(X) is a function of independent random variables X = (X1, . . . , Xn). Here the well known bounded differences inequality (also called McDiarmid… (More)