Détails du livre
Format
Broché
Pages
407
Langue
Anglais
Publié
Jan 1, 2010
Éditeur
Orient Blackswan
Édition
1
ISBN-10
8173717141
ISBN-13
9788173717147
Description
Dimitri P. Bertsekas delves deep into the intricate world of convex optimization, presenting a comprehensive guide that bridges theory and practical applications. The author meticulously outlines the foundational concepts of convex sets and functions, enabling readers to grasp the pivotal aspects that make this field so essential in mathematics and engineering.
With a keen focus on the geometric interpretation of optimization problems, the book emphasizes critical techniques and methodologies used to solve complex issues. Bertsekas expertly navigates through advanced topics, ensuring that the material is not only accessible to newcomers but also enriching for seasoned practitioners looking to refine their understanding.
Real-world applications are woven throughout the chapters, illustrating how convex optimization can be applied to various disciplines such as economics, finance, and machine learning. Each section is thoughtfully constructed, with clear examples that reinforce the theoretical underpinnings while demonstrating their practical relevance.
Readers will appreciate the balance of rigor and readability that characterizes this work. Through engaging explanations and detailed explorations of algorithms, Bertsekas fosters a deeper appreciation for the significance of convex optimization in contemporary research and everyday problem-solving.
With a keen focus on the geometric interpretation of optimization problems, the book emphasizes critical techniques and methodologies used to solve complex issues. Bertsekas expertly navigates through advanced topics, ensuring that the material is not only accessible to newcomers but also enriching for seasoned practitioners looking to refine their understanding.
Real-world applications are woven throughout the chapters, illustrating how convex optimization can be applied to various disciplines such as economics, finance, and machine learning. Each section is thoughtfully constructed, with clear examples that reinforce the theoretical underpinnings while demonstrating their practical relevance.
Readers will appreciate the balance of rigor and readability that characterizes this work. Through engaging explanations and detailed explorations of algorithms, Bertsekas fosters a deeper appreciation for the significance of convex optimization in contemporary research and everyday problem-solving.