Søgeresultater - learning algorithm

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  1. Today's TBB af Voss, Michael J., Reinders, James R.

    Udgivet 2025
    “...It then introduces the major components of TBB including parallel algorithms, flow graphs, and task groups that help you fully leverage the power of multicore systems. ...”
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  2. MATLAB Roadmap to Applications af Chen, Yi, Huang, Long

    Udgivet 2025
    “...The book's structure is carefully crafted to facilitate step-by-step learning, with each chapter building upon previous knowledge. ...”
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  3. KI-unterstützte hybride Modellierung von Emissionen im hochtransienten Motorbetrieb af Gehra, Tobias

    Udgivet 2025
    Fag: “...thema EDItEUR::U Computing and Information Technology::UM Computer programming / software engineering::UMB Algorithms and data structures...”
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  4. Digital Capitalism and its Limits af Bauwens, Michel, Castel-Branco, Ruth, Daaboul, Mayssam, Duncan, Jane, Kranjc, Rok, Kwet, Michael, Mohubetswane Mashilo, Alex, Mokhema, Seipati, Nana, Constantine N, Satgoor, Ujala, Siwawa, Vincent, Webster, Edward

    Udgivet 2025
    “...They question the dangerous technotopian imaginary shaping this digital techno-shift, the implications of algorithmic data extractivism, the securitisation of already weak market democracies, the social consequences of digital learning, lack of regulation, and the power dynamics in the labour process. ...”
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  5. Augmented Education in the Global Age

    Udgivet 2025
    Fag: “...Artificial Intelligence and the Future of Learning and Work...”
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  6. Metoda pomiaru wybranych osiągów naziemnych samolotu z wykorzystaniem algorytmów atencji oraz ekscytacji w modelu q-kształtnej sztucznej sieci neuronowej af Tomiło, Paweł

    Udgivet 2025
    “...These initial tests focused on collecting data for learning and improving the effectiveness of the neural network. ...”
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  7. Resourceful ageing

    Udgivet 2025
    “...The results offer the reader a categorized set of strategies for supporting resourcefulness in older people’s everyday lives; methodological considerations on algorithmic design practices and the role of machine learning in support of improvisation; and, relevant design tools and techniques. ...”
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  8. Federated Learning

    Udgivet 2025
    “...It examines the distinctions between FL and traditional distributed learning paradigms through a comparative lens. The chapters explore key concepts, algorithmic advancements, and computational strategies that underpin the development of FL, with a particular focus on deep learning applications. ...”
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  9. Maritime Cybersecurity

    Udgivet 2025
    “...The authors present mechanisms for early detection and prevention of cyber-attacks, as well as security protocols based on testbed nautical simulator experiments, machine learning algorithms and artificial intelligence applications. ...”
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  10. Multi Agent Systems

    Udgivet 2025
    “...This book brings together researchers working in several fields that cover the techniques, the challenges and the applications of multi-agent systems in a wide variety of aspects related to learning algorithms for different devices such as vehicles, robots and drones, computational optimization to reach a more efficient energy distribution in power grids and the use of social networks and decision strategies applied to the smart learning and education environments in emergent countries. ...”
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  11. Entropy in Machine Learning Applications

    Udgivet 2025
    “...The aim of this reprint is to inform readers of the latest developments in methods and applications of machine learning and deep learning in certain fields, including the following: a semantically enhanced social network user alignment algorithm to perform user alignment; a congestion control mechanism based on deep reinforcement learning; problem solving involving low-accuracy, large-entropy perturbation; information loss in the calculation process of fault feature parameters of rolling bearing; a hybrid recommendation model combining autoencoder and latent feature analysis techniques; extracting knowledge from published papers and reports on drilling to guide the control of wells; an improved binary golden jackal optimization algorithm; water quality prediction based on machine learning and comprehensive weighting methods; redundancy of crossentropy calculation in deep learning of classifiers; automatic vertebral rotation angle measurement of vertebrae using an improved transformer network; defining suitable graph contrastive learning through applications of graph information bottlenecks and structural entropy theories; and a comprehensive examination of the latest advancements in deep learning methodologies. ...”
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