Yuri S. Popkov, Alexey Yu. Popkov, Yuri A. Dubnov

eBook, ePUB

Entropy Randomization in Machine Learning (eBook, ePUB)

Beschreibung

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).

Technische Details

• Geräte: eReader
• mit Kopierschutz

Barrierefreiheit

• Text-to-Speech
• E-Mail des Verlags für Barrierefreiheitsfragen: [e-mail]
• ARIA-Rollen für verbesserte strukturelle Navigation
• Navigation über vor-/zurück-Elemente ohne Inhaltsverzeichnis
• Seitennummerierung folgt dem gedruckten Werk
• Mathematische Inhalte in MathML für assistive Technologien
• Kurze Alternativtexte für nicht-textuelle Inhalte vorhanden
• Text und Medien in logischer Lesereihenfolge angeordnet
• Navigierbarer Index mit direktem Zugriff auf Indexbegriffe
• Navigierbares Inhaltsverzeichnis für direkten Zugriff auf Text und Medien

Autor

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.

Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 392
• Erscheinungstermin: 9. August 2022
• Englisch
• ISBN-13: 9781000628739
• Artikelnr.: 64189589