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Sparse Polynomial Optimization Theory by Magron Victor (11 results)
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Sparse Polynomial Optimization: Theory And Practice
Published by World Scientific Europe Ltd, 2023
ISBN 10: 180061294X ISBN 13: 9781800612945
Language: English
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
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US$ 118.01
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Sparse Polynomial Optimization: Theory And Practice (Series On Optimization And Its Applications)
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Sparse Polynomial Optimization : Theory and Practice
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Sparse Polynomial Optimization : Theory and Practice
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Sparse Polynomial Optimization: Theory and Practice
Published by World Scientific Pub Co Inc, 2023
ISBN 10: 180061294X ISBN 13: 9781800612945
Language: English
US$ 143.66
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Add to basketHardcover. Condition: Brand New. 200 pages. 9.00x6.00x0.56 inches. In Stock.
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Sparse Polynomial Optimization: Theory And Practice
Published by World Scientific Europe Ltd, 2023
ISBN 10: 180061294X ISBN 13: 9781800612945
Language: English
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
US$ 122.53
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Add to basketHardback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
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Sparse Polynomial Optimization: Theory and Practice
Published by WORLD SCIENTIFIC PUB EUROPE, 2023
ISBN 10: 180061294X ISBN 13: 9781800612945
Language: English
US$ 137.64
Convert currencyUS$ 56.46 shipping from Germany to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. KlappentextMany applications, including computer vision, computer arithmetic, deep learning, entanglement in quantum information, graph theory and energy networks, can be successfully tackled within the framework of polynomial optimizati.
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Add to basketBuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Many applications, including computer vision, computer arithmetic, deep learning, entanglement in quantum information, graph theory and energy networks, can be successfully tackled within the framework of polynomial optimization, an emerging field with growing research efforts in the last two decades. One key advantage of these techniques is their ability to model a wide range of problems using optimization formulations. Polynomial optimization heavily relies on the moment-sums of squares (moment-SOS) approach proposed by Lasserre, which provides certificates for positive polynomials. On the practical side, however, there is 'no free lunch' and such optimization methods usually encompass severe scalability issues. Fortunately, for many applications, including the ones formerly mentioned, we can look at the problem in the eyes and exploit the inherent data structure arising from the cost and constraints describing the problem.This book presents several research efforts to resolve this scientific challenge with important computational implications. It provides the development of alternative optimization schemes that scale well in terms of computational complexity, at least in some identified class of problems. It also features a unified modeling framework to handle a wide range of applications involving both commutative and noncommutative variables, and to solve concretely large-scale instances. Readers will find a practical section dedicated to the use of available open-source software libraries.This interdisciplinary monograph is essential reading for students, researchers and professionals interested in solving optimization problems with polynomial input data.
