Concentration inequalities are fundamental tools in probabilistic combinatorics and theoretical computer science for proving that random functions are near their means.
Dec 23, 2012
In this paper we prove a variant of the bounded differences inequality which can be used to establish concentration of functions f(X) where (i) the typical ...
Dec 23, 2012 · Here the well known bounded differences inequality (also called McDi- armid's or Hoeffding–Azuma inequality) establishes sharp concentration if ...
It seems to be a convenient tool (e.g., to simplify/shorten proofs). Some applications of the typical bounded differences inequality. Additive combinatorics.
A variant of the bounded differences inequality which can be used to establish concentration of functions f(X) where (i) the typical changes are small, ...
In this paper we prove a variant of the bounded differences inequality which can be used to establish concentration of functions f(X) where (i) the typical ...
Oct 22, 2024 · In this paper we prove a variant of the bounded differences inequality which can be used to establish concentration of functions f(X) where (i) ...
On the method of bounded differences. Published online by Cambridge University Press: 05 August 2013. By Colin McDiarmid. Edited by J. Siemons.
Missing: Typical | Show results with:Typical
One key aspect of this inequality is that it relies on a simple condition that (a) is easy to check and (b) coincides with heuristic considerations as to why ...
Oct 10, 2022 · Is there an example, where the bounded difference property gives better concentration than what we get from using the sub-gaussian bound?
Missing: Typical | Show results with:Typical