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Communication Dans Un Congrès Année : 2012

Robust Eigenvector of a Stochastic Matrix with Application to PageRank

Résumé

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.

Dates et versions

hal-00981872 , version 1 (23-04-2014)

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Anatoli B. Juditsky, Boris Polyak. Robust Eigenvector of a Stochastic Matrix with Application to PageRank. CDC 2012 - IEEE 51st Annual Conference on Decision and Control, Dec 2012, Maui, United States. pp.3171-3176, ⟨10.1109/CDC.2012.6426431⟩. ⟨hal-00981872⟩
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