Robust Eigenvector of a Stochastic Matrix with Application to PageRank
Optimization and Control
2012-06-22 v1
Abstract
We discuss a definition of robust dominant eigenvector of a family of stochastic matrices. Our focus is on application to ranking problems, where the proposed approach can be seen as a robust alternative to the standard PageRank technique. The robust eigenvector computation is reduced to a convex optimization problem. We also propose a simple algorithm for robust eigenvector approximation which can be viewed as a regularized power method with a special stopping rule.
Cite
@article{arxiv.1206.4897,
title = {Robust Eigenvector of a Stochastic Matrix with Application to PageRank},
author = {Anatoli Juditsky and Boris Polyak},
journal= {arXiv preprint arXiv:1206.4897},
year = {2012}
}