Andersen Martin, Hansson Anders. Optimization for Learning and Control

John Wiley & Sons, 2023. — 435 p. — ISBN: 9781119809135.Optimization for Learning and Control describes how optimization is used in these domains, giving a thorough introduction to unsupervised learning, supervised learning, and reinforcement learning, with an emphasis on optimization methods for large-scale learning and control problems. Several application 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 Master’ 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 MMaster’sstudents in a coherent way. The focus is on basic algorithmic principles and trade-offs. 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.Introductory Part.
Optimization.
Optimal Control.
Learning.