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"Offering a fundamental basis in kernel-based learning theory, this book covers both statistical and algebraic principles. It provides over 30 major theorems for kernel-based supervised and unsupervised learning models. The first of the theorems establishes a condition, arguably necessary and sufficient, for the kernelization of learning models. In addition, several other theorems are devoted to proving mathematical equivalence between seemingly unrelated models. With over 25 closed-form and iterative algorithms, the book provides a step-by-step guide to algorithmic procedures and analysing which factors to consider in tackling a given problem, enabling readers to improve specifically designed learning algorithms, build models for new applications and develop efficient techniques suitable for green machine learning technologies. Numerous real-world examples and over 200 problems, several of which are Matlab-based simulation exercises, make this an essential resource for graduate students and professionals in computer science, electrical and biomedical engineering. Solutions to problems are provided online for instructors"-- "Provides an overview of the broad spectrum of applications and problem formulations for kernel-based unsupervised and supervised learning methods. The dimension of the original vector space, along with its Euclidean inner product, often proves to be highly inadequate for complex data analysis. In order to provide a more e

Support vector machines. --- Machine learning. --- Kernel functions. --- Functions, Kernel --- Functions of complex variables --- Geometric function theory --- Learning, Machine --- Artificial intelligence --- Machine theory --- SVMs (Algorithms) --- Algorithms --- Kernel functions --- Supervised learning (Machine learning) --- COMPUTERS / Computer Vision & Pattern Recognition. --- Support vector machines --- Machine learning

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Social sciences (general) --- Computer assisted instruction --- Computer architecture. Operating systems --- Information systems --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- computervisie --- informatica --- sociale wetenschappen --- computerondersteund onderwijs --- database management --- KI (kunstmatige intelligentie) --- computernetwerken

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Social sciences (general) --- Computer assisted instruction --- Programming --- Computer architecture. Operating systems --- Information systems --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- computervisie --- applicatiebeheer --- apps --- informatica --- sociale wetenschappen --- computerondersteund onderwijs --- database management --- KI (kunstmatige intelligentie) --- architectuur (informatica)

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This three-volume set constitutes the refereed proceedings of the 14th International Conference on Knowledge Science, Engineering and Management, KSEM 2021, held in Tokyo, Japan, in August 2021. The 164 revised full papers were carefully reviewed and selected from 492 submissions. The contributions are organized in the following topical sections: knowledge science with learning and AI; knowledge engineering research and applications; knowledge management with optimization and security.

Social sciences (general) --- Computer assisted instruction --- Computer science --- Programming --- Computer architecture. Operating systems --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- applicatiebeheer --- apps --- informatica --- sociale wetenschappen --- computerondersteund onderwijs --- algoritmen --- KI (kunstmatige intelligentie) --- computernetwerken --- architectuur (informatica)

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