Cart (Loading....) | Create Account
Close category search window
 

A Chernoff bound for random walks on expander graphs

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Gillman, D. ; Inst. for Math. & Applications, Minnesota Univ., Minneapolis, MN, USA

We consider a finite random walk on a weighted graph G; we show that the sample average of visits to a set of vertices A converges to the stationary probability π(A) with error probability exponentially small in the length of the random walk and the square of the size of the deviation from π(A). The exponential bound is in terms of the expansion of G and improves previous results. We show that the method of taking the sample average from one trajectory is a more efficient estimate of π(A) than the standard method of generating independent sample points from several trajectories. Using this more efficient sampling method, we improve the algorithms of Jerrum and Sinclair (1989) for approximating the number of perfect matchings in a dense graph and for approximating the partition function of an Ising system. We also give a fast estimate of the entropy of a random walk on an unweighted graph

Published in:

Foundations of Computer Science, 1993. Proceedings., 34th Annual Symposium on

Date of Conference:

3-5 Nov 1993

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.