convex optimization theory (24 Ergebnisse)

Soft cover. Zustand: New. The book Convex Optimization Theory provides an insightful concise and rigorous treatment of the basic theory of convex sets and functions in finite dimensions and the analyticalgeometrical foundations of convex optimization and duality theory The convexity theory is developed first in a simple accessible manner using easily visualized proofs The focus then shifts to a transparent geometrical line of analysis to develop the fundamental duality between descriptions of convex sets and functions in terms of points and in terms of hyperplanes Finally convexity theory and abstract duality are applied to problems of constrained optimization Fenchel and conic duality and game theory to develop the sharpest possible duality results within a highly visual geometric framework Key features Rigorous and comprehensive development of the theory of convex sets and functions in the classical tradition of Fenchel and Rockafellar A geometric and highly visual treatment of convex optimization problems including duality existence of solutions and optimality conditions An insightful and comprehensive presentation of minimax theory and zero sum games and its connection with duality Contains many examples and illustrations in the text Inclusion of many examples illustrations exercises with complete solutions and a supplementary chapter on the most popular convex optimization algorithms Useable as a standalone text for a theoretically-oriented class on convex analysis and optimization or as a theoretical supplement to either an applicationsconvex optimization models class or a nonlinear programming class 420 pp.

Zustand: New. pp. xii + 407.

paperback. Zustand: New.

Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Zustand: New. In English.

Zustand: Good. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions.

Hardcover. Ex-library with stamp and library-signature. GOOD condition, some traces of use. Ancien Exemplaire de bibliothèque avec signature et cachet. BON état, quelques traces d'usure. Ehem. Bibliotheksexemplar mit Signatur und Stempel. GUTER Zustand, ein paar Gebrauchsspuren. 90 BOR 9780387989402 Sprache: Englisch Gewicht in Gramm: 550.

Hardcover. X, 273 S. Ehem. Bibliotheksexemplar mit Signatur und Stempel. GUTER Zustand, ein paar Gebrauchsspuren. Ex-library with stamp and library-signature. GOOD condition, some traces of use. C-01332 9780387989402 Sprache: Englisch Gewicht in Gramm: 550.

Zustand: New. In.

Hardcover. Zustand: As New. No Jacket. Pages are clean and are not marred by notes or folds of any kind. ~ ThriftBooks: Read More, Spend Less 1.15.

Zustand: New. In English.

Zustand: New. In English.

Hardcover. Zustand: Brand New. 256 pages. 9.25x6.25x0.75 inches. In Stock.

Zustand: New.

Zustand: Very Good. Most items will be dispatched the same or the next working day. A copy that has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.

Hardcover. Zustand: Brand New. 256 pages. 9.25x6.25x0.75 inches. In Stock.

Zustand: New.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Optimization is a rich and thriving mathematical discipline. The theory underlying current computational optimization techniques grows ever more sophisticated. The powerful and elegant language of convex analysis unifies much of this theory. The aim of this book is to provide a concise, accessible account of convex analysis and its applications and extensions, for a broad audience. It can serve as a teaching text, at roughly the level of first year graduate students. While the main body of the text is self-contained, each section concludes with an often extensive set of optional exercises. The new edition adds material on semismooth optimization, as well as several new proofs that will make this book even more self-contained.

Hardcover. Zustand: Brand New. 2nd edition. 310 pages. 9.25x6.25x1.00 inches. In Stock.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Optimization is a rich and thriving mathematical discipline. The theory underlying current computational optimization techniques grows ever more sophisticated. The powerful and elegant language of convex analysis unifies much of this theory. The aim of this book is to provide a concise, accessible account of convex analysis and its applications and extensions, for a broad audience. It can serve as a teaching text, at roughly the level of first year graduate students. While the main body of the text is self-contained, each section concludes with an often extensive set of optional exercises. The new edition adds material on semismooth optimization, as well as several new proofs that will make this book even more self-contained.

Paperback. Zustand: Brand New. 138 pages. 9.25x6.00x0.50 inches. In Stock.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This work is intended to serve as a guide for graduate students and researchers who wish to get acquainted with the main theoretical and practical tools for the numerical minimization of convex functions on Hilbert spaces. Therefore, it contains the main tools that are necessary to conduct independent research on the topic. It is also a concise, easy-to-follow and self-contained textbook, which may be useful for any researcher working on related fields, as well as teachers giving graduate-level courses on the topic. It will contain a thorough revision of the extant literature including both classical and state-of-the-art references.

Hardcover. Zustand: Brand New. 416 pages. 9.18x6.12x9.45 inches. In Stock.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This volume includes chapters on topics presented at the conference on Recent Trends in Convex Optimization: Theory, Algorithms and Applications (RTCOTAA-2020), held at the Department of Mathematics, Indian Institute of Technology Patna, Bihar, India, from 29-31 October 2020. Itdiscusses a comprehensive exploration of the realm of optimization, encompassing both the theoretical underpinnings and the multifaceted real-life implementations of the optimization theory. It meticulously features essential optimization concepts, such as convex analysis, generalized convexity, monotonicity, etc., elucidating their theoretical advancements and significance in the optimization sphere. Multiobjective optimization is a pivotal topic which addresses the inherent difficulties faced in conflicting objectives. The book delves into various theoretical concepts and covers some practical algorithmic approaches to solve multiobjective optimization, such as the line search and the enhanced non-monotone quasi-Newton algorithms. It also deliberates on several other significant topics in optimization, such as the perturbation approach for vector optimization, and solution methods for set-valued optimization. Nonsmooth optimization is extensively covered, with in-depth discussions on various well-known tools of nonsmooth analysis, such as convexificators, limiting subdifferentials, tangential subdifferentials, quasi-differentials, etc.Notable optimization algorithms, such as the interior point algorithm and Lemke's algorithm, are dissected in detail, offering insights into their applicability and effectiveness. The book explores modern applications of optimization theory, for instance, optimized image encryption, resource allocation, target tracking problems, deep learning, entropy optimization, etc. Ranging from gradient-based optimization algorithms to metaheuristic approaches such as particle swarm optimization, the book navigates through the intersection of optimization theory and deep learning, thereby unravelling new research perspectives in artificial intelligence, machine learning and other fields of modern science. Designed primarily for graduate students and researchers across a variety of disciplines such as mathematics, operations research, electrical and electronics engineering, computer science, robotics, deep learning, image processing and artificial intelligence, this book serves as a comprehensive resource for someone interested in exploring the multifaceted domain of mathematical optimization and its myriad applications.