Standard

Randomized Algorithms in Automatic Control and Data Mining. / Granichin, O.; Volkovich, Z.V.; Toledano-Kitai, D.

Berlin, Heidelberg : Springer Nature, 2015. 251 p. (Intelligent Systems Reference Library; Vol. 67).

Research output: Book/Report/Anthology › Book › peer-review

Harvard

Granichin, O, Volkovich, ZV & Toledano-Kitai, D 2015, Randomized Algorithms in Automatic Control and Data Mining. Intelligent Systems Reference Library, vol. 67, vol. 67, Springer Nature, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54786-7, https://doi.org/10.1007/978-3-642-54786-7

APA

Granichin, O., Volkovich, Z. V., & Toledano-Kitai, D. (2015). Randomized Algorithms in Automatic Control and Data Mining. (Intelligent Systems Reference Library; Vol. 67). Springer Nature. https://doi.org/10.1007/978-3-642-54786-7, https://doi.org/10.1007/978-3-642-54786-7

Vancouver

Granichin O, Volkovich ZV, Toledano-Kitai D. Randomized Algorithms in Automatic Control and Data Mining. Berlin, Heidelberg: Springer Nature, 2015. 251 p. (Intelligent Systems Reference Library). https://doi.org/10.1007/978-3-642-54786-7, https://doi.org/10.1007/978-3-642-54786-7

Author

Granichin, O. ; Volkovich, Z.V. ; Toledano-Kitai, D. / Randomized Algorithms in Automatic Control and Data Mining. Berlin, Heidelberg : Springer Nature, 2015. 251 p. (Intelligent Systems Reference Library).

BibTeX

@book{f3f4f24dcae545c2b35e02af0d7e0d01,
title = "Randomized Algorithms in Automatic Control and Data Mining",
abstract = "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.",
keywords = "Intelligent Systems , Randomized Algorithms in Data Mining, Randomized Algorithms in Automatic Control ",
author = "O. Granichin and Z.V. Volkovich and D. Toledano-Kitai",
note = "https://link.springer.com/book/10.1007/978-3-642-54786-7 ",
year = "2015",
doi = "10.1007/978-3-642-54786-7",
language = "English",
isbn = "978-3-642-54785-0",
volume = "67",
series = "Intelligent Systems Reference Library",
publisher = "Springer Nature",
address = "Germany",

}

RIS

TY - BOOK

T1 - Randomized Algorithms in Automatic Control and Data Mining

AU - Granichin, O.

AU - Volkovich, Z.V.

AU - Toledano-Kitai, D.

N1 - https://link.springer.com/book/10.1007/978-3-642-54786-7

PY - 2015

Y1 - 2015

N2 - 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.

AB - 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.

KW - Intelligent Systems

KW - Randomized Algorithms in Data Mining

KW - Randomized Algorithms in Automatic Control

U2 - 10.1007/978-3-642-54786-7

DO - 10.1007/978-3-642-54786-7

M3 - Book

SN - 978-3-642-54785-0

VL - 67

T3 - Intelligent Systems Reference Library

BT - Randomized Algorithms in Automatic Control and Data Mining

PB - Springer Nature

CY - Berlin, Heidelberg

ER -

ID: 9655374