Entropy Randomization in Machine Learning by Yuri S Popkov
Entropy Randomization in Machine Learning presents a new approach to machine learning - entropy randomization - to obtain optimal solutions under uncertainty (uncertain data and models of the objects under study).-
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Yuri S. Popkov: Doctor of Engineering, Professor, Academician of Russian Academy of Sciences; Chief Researcher at Federal Research Center “Computer Science and Control,” Russian Academy of Sciences; Chief Researcher at Trapeznikov Institute of Control Sciences, Russian Academy of Sciences; Professor at Lomonosov Moscow State University. Author of more than 250 scientific publications, including 15 monographs. His research interests include stochastic dynamic systems, optimization, machine learning, and macrosystem modeling.
Alexey Yu. Popkov: Candidate of Sciences, Leading Researcher at Federal Research Center “Computer Science and Control,” Russian Academy of Sciences; author of 47 scientific publications. His research interests include software engineering, high-performance computing, data mining, machine learning, and entropy methods.
Yuri A. Dubnov: MSc in Physics, Researcher at Federal Research Center “Computer Science and Control,” Russian Academy of Sciences. Author of more than 18 scientific publications. His research interests include machine learning, forecasting, randomized approaches, and Bayesian estimation.
| SKU | Unavailable |
| ISBN 13 | 9781032306285 |
| ISBN 10 | 1032306289 |
| Title | Entropy Randomization in Machine Learning |
| Author | Yuri S Popkov |
| Series | Chapman And Hall Crc Machine Learning And Pattern Recognition |
| Condition | Unavailable |
| Binding Type | Hardback |
| Publisher | Taylor & Francis Ltd |
| Year published | 2022-08-09 |
| Number of pages | 392 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |