Saddle point mirror descent algorithm for the robust PageRank problem
| Autor: | A. V. Nazin, A. A. Tremba |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
0209 industrial biotechnology
021103 operations research Optimization problem 0211 other engineering and technologies Mirror descent 02 engineering and technology Function (mathematics) Square (algebra) law.invention Euclidean distance 020901 industrial engineering & automation PageRank Control and Systems Engineering law Saddle point Electrical and Electronic Engineering Algorithm Saddle Mathematics |
| Zdroj: | Automation and Remote Control. 77:1403-1418 |
| ISSN: | 1608-3032 0005-1179 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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