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Modern Optimization Methods

Edition en anglais

Qingna LI

  • EDP Sciences

  • Paru le : 13/11/2023
With the fast development of big data and artificial intelligence, a natural question is how do we analyze data more efficiently? One of the efficient... > Lire la suite
65,99 €
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With the fast development of big data and artificial intelligence, a natural question is how do we analyze data more efficiently? One of the efficient ways is to use optimization. What is optimization? Optimization exists everywhere. People optimize. As long as you have choices, you do optimization. Optimization is the key of operations research. This book introduces the basic definitions and theory about numerical optimization, including optimality conditions for unconstrained and constrained optimization, as well as algorithms for unconstrained and constrained problems.
Moreover, it also includes the nonsmooth Newton's method, which plays an important role in large-scale numerical optimization. Finally, based on the author's research experiences, several latest applications about optimization are introduced, including optimization algorithms for hypergraph matching, support vector machine and bilevel optimization approach for hyperparameter selection in machine learning.
With these optimization tools, one can deal with data more efficiently.

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  • Caractéristiques du format PDF
    • Pages : 157
    • Taille : 6 769 Ko
    • Protection num. : Digital Watermarking

À propos de l'auteur

Biographie de Qingna LI

Qingna LI is a full professor in School of Mathematics and Statistics, Beijing Institute of Technology. Her research interests include continuous optimization, specifically in matrix optimization, sparse optimization and the applications in various areas including wireless communication, statistics, artificial intelligence and so on.
Qingna LI - Modern Optimization Methods.
Modern Optimization Methods
Qingna LI
65,99 €
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