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Randomized Algorithms in Automatic Control and Data Mining (Hardcover, 2015 ed.): Oleg Granichin, Zeev (Vladimir) Volkovich,... Randomized Algorithms in Automatic Control and Data Mining (Hardcover, 2015 ed.)
Oleg Granichin, Zeev (Vladimir) Volkovich, Dvora Toledano-Kitai
R4,443 R3,586 Discovery Miles 35 860 Save R857 (19%) Ships in 12 - 19 working days

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.

Randomized Algorithms in Automatic Control and Data Mining (Paperback, Softcover reprint of the original 1st ed. 2015): Oleg... Randomized Algorithms in Automatic Control and Data Mining (Paperback, Softcover reprint of the original 1st ed. 2015)
Oleg Granichin, Zeev (Vladimir) Volkovich, Dvora Toledano-Kitai
R3,614 Discovery Miles 36 140 Ships in 10 - 15 working days

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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