Optimization for Learning and Control (Hardcover)

Idioma: inglés

Editorial: John Wiley & Sons Inc, New York, 2023

1119809134 / 9781119809135

Librería: CitiRetail, Stevenage, Reino UnidoCitiRetail

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Hardcover. Optimization for Learning and Control Comprehensive resource providing a masters level introduction to optimization theory and algorithms for learning and control Optimization for Learning and Control describes how optimization is used in these domains, giving a thorough introduction to both unsupervised learning, supervised learning, and reinforcement learning, with an emphasis on optimization methods for large-scale learning and control problems. Several applications areas are also discussed, including signal processing, system identification, optimal control, and machine learning. Today, most of the material on the optimization aspects of deep learning that is accessible for students at a Masters level is focused on surface-level computer programming; deeper knowledge about the optimization methods and the trade-offs that are behind these methods is not provided. The objective of this book is to make this scattered knowledge, currently mainly available in publications in academic journals, accessible for Masters students in a coherent way. The focus is on basic algorithmic principles and trade-offs. Optimization for Learning and Control covers sample topics such as: Optimization theory and optimization methods, covering classes of optimization problems like least squares problems, quadratic problems, conic optimization problems and rank optimization.First-order methods, second-order methods, variable metric methods, and methods for nonlinear least squares problems.Stochastic optimization methods, augmented Lagrangian methods, interior-point methods, and conic optimization methods.Dynamic programming for solving optimal control problems and its generalization to reinforcement learning.How optimization theory is used to develop theory and tools of statistics and learning, e.g., the maximum likelihood method, expectation maximization, k-means clustering, and support vector machines.How calculus of variations is used in optimal control and for deriving the family of exponential distributions. Optimization for Learning and Control is an ideal resource on the subject for scientists and engineers learning about which optimization methods are useful for learning and control problems; the text will also appeal to industry professionals using machine learning for different practical applications. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

N° de ref. del artículo 9781119809135

Título
Optimization for Learning and Control (Hardcover)
Autor
Martin Andersen
Editorial
John Wiley & Sons Inc, New York
Año de publicación
2023
Estado
new
Encuadernación
Hardcover
Idioma
inglés
ISBN 10
1119809134
ISBN 13
9781119809135

CitiRetail

Stevenage, Reino Unido

Vendedor de 5 estrellas

Vendedor de IberLibro desde 29 de junio de 2022

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Primer artículoEUR 43,88EUR 43,88
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