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Herausgeber: 
  • P. Balasubramaniam
  • P. Raveendran
  • Kuru Ratnavelu
  • G. Nagamani
  • Sasi Gopalan
  • Mathematical Techniques for Machine Learning and Quantum Computing: IWCMLQC-2024, Kochi, Kerala, India, December 5-7 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Vorankündigung
    Veröffentlichung:  ANGEKÜNDIGT (Oktober 2026)  
    Genre:  Schulbücher 
     
    Applications of Mathematics / Artificial Intelligence / Corona graphs / domination number / Fuzzy Sets and Logic / Graph Theory / Image Processing and Computer Vision / Intuitionistic Fuzzy Set
    ISBN:  9789819239115 
    EAN-Code: 
    9789819239115 
    Verlag:  Springer EN 
    Einband:  Gebunden  
    Sprache:  English  
    Dimensionen:  H 235 mm / B 155 mm / D  
    Seiten:  232 
    Illustration:  II, 232 p. 57 illus., 40 illus. in color., schwarz-weiss Illustrationen, farbige Illustrationen 
    Zus. Info:  EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025. 
    Bewertung: Keine Bewertung vor Veröffentlichung möglich.
    Inhalt:
    This book presents a collection of research papers presented at the International Workshop and International Conference on Mathematical Techniques for Machine Learning and Quantum Computing (IWCMLQC-2024), held at the Cochin University of Science and Technology (CUSAT), Kochi, Kerala, India, from December 5-7, 2024. Chapters discuss both theoretical and applied aspects of topics in mathematics, reflecting its broad interdisciplinary scope. This book covers diverse fields, including graph theory, fuzzy logic, functional analysis, optimization, and data science, highlighting the crucial role of mathematics in advancing computational methods, artificial intelligence, medical imaging, and cryptographic security. It provides new insights into mathematical structures, proposes innovative algorithms, and presents applications addressing contemporary challenges across science and engineering.
    This book provides an extensive discussion on quantum algorithms and demonstrates the potential to redefine computational intelligence. By integrating concepts from quantum computing, machine learning, and artificial intelligence, it presents a forward-looking perspective on emerging technologies. The discussions encourage readers to explore advanced research directions and gain a deeper understanding of upcoming computational frameworks. It also makes a significant contribution to the evolving landscape of intelligent computing.

      



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