Randomized Algorithms in Automatic Control and Data Mining

✍ Scribed by Oleg Granichin, Zeev (Vladimir) Volkovich, Dvora Toledano-Kitai (auth.)

• Publisher: Springer-Verlag Berlin Heidelberg
• Year: 2015
• Tongue: English
• Leaves: 268
• Series: Intelligent Systems Reference Library 67
• Edition: 1
• Category: Library

✦ Synopsis

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.

✦ Table of Contents

Front Matter....Pages 1-22
Front Matter....Pages 1-2
Feedback, Averaging and Randomization in Control and Data Mining....Pages 3-22
Historical Overview....Pages 23-46
Front Matter....Pages 47-49
Randomized Stochastic Approximation....Pages 51-74
Linear Models....Pages 75-105
Randomized Control Strategies....Pages 107-127
Front Matter....Pages 129-130
Clustering....Pages 131-161
Cluster Validation....Pages 163-228
Back Matter....Pages 229-249

✦ Subjects

Computational Intelligence; Control; Data Mining and Knowledge Discovery