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Статья

Saddle point mirror descent algorithm for the robust PageRank problem

Automation and Remote Control. 2016. Vol. 77. No. 8. P. 1403-1418.
Nazin A., Tremba A.

In order to solve robust PageRank problem a saddle-point Mirror Descent algorithm for solving convex-concave optimization problems is enhanced and studied. The algorithm is based on two proxy functions, which use specificities of value sets to be optimized on (min-max search). In robust PageRank case the ones are entropy-like function and square of Euclidean norm. The saddle-point Mirror Descent algorithm application to robust PageRank leads to concrete complexity results, which are being discussed alongside with illustrative numerical example.