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Randomized Algorithms in Automatic Control and Data Mining [electronic resource] / by Oleg Granichin, Zeev (Vladimir) Volkovich, Dvora Toledano-Kitai.

By: Granichin, Oleg [author.].
Contributor(s): Volkovich, Zeev (Vladimir) [author.] | Toledano-Kitai, Dvora [author.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Intelligent Systems Reference Library: 67Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2015Description: XXIV, 251 p. 99 illus., 19 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783642547867.Subject(s): Engineering | Data mining | Computational intelligence | Control engineering | Engineering | Computational Intelligence | Control | Data Mining and Knowledge DiscoveryAdditional physical formats: Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online
Contents:
Randomized algorithms -- Randomization in estimation, identification and filtering problems under arbitrary external noises -- Data mining.
In: Springer eBooksSummary: In the fields of data mining and control, the huge amount of unstructured data and the presence of uncertainty in system descriptions have always been critical issues. The book Randomized Algorithms in Automatic Control and Data Mining introduces the readers to the fundamentals of randomized algorithm applications in data mining (especially clustering) and in automatic control synthesis. The methods proposed in this book guarantee that the computational complexity of classical algorithms and the conservativeness of standard robust control techniques will be reduced. It is shown that when a problem requires "brute force" in selecting among options, algorithms based on random selection of alternatives offer good results with certain probability for a restricted time and significantly reduce the volume of operations.
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Randomized algorithms -- Randomization in estimation, identification and filtering problems under arbitrary external noises -- Data mining.

In the fields of data mining and control, the huge amount of unstructured data and the presence of uncertainty in system descriptions have always been critical issues. The book Randomized Algorithms in Automatic Control and Data Mining introduces the readers to the fundamentals of randomized algorithm applications in data mining (especially clustering) and in automatic control synthesis. The methods proposed in this book guarantee that the computational complexity of classical algorithms and the conservativeness of standard robust control techniques will be reduced. It is shown that when a problem requires "brute force" in selecting among options, algorithms based on random selection of alternatives offer good results with certain probability for a restricted time and significantly reduce the volume of operations.

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