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We discuss a definition of robust dominant eigenvector of a family ofstochastic matrices. Our focus is on application to ranking problems, where theproposed approach can be seen as a robust alternative to the standard PageRanktechnique. The robust eigenvector computation is reduced to a convexoptimization problem. We also propose a simple algorithm for robust eigenvectorapproximation which can be viewed as a regularized power method with a specialstopping rule.

Robust Eigenvector of a Stochastic Matrix with Application to PageRank