First Order Methods Optimization by Amir Beck (18 results)

Language: English
Published by SIAM-Society for Industrial and Applied Mathematicsq, 2017
- Softcover
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Language: English
Published by SIAM-Society for Industrial and Applied Mathematicsq, 2017
- Softcover
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Language: English
Published by MP-SIA SIAM - Society for Industrial and Applied M, 2017
- Softcover
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Language: English
Published by SIAM-Society for Industrial and Applied Mathematicsq, 2017
- Softcover
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Language: English
Published by SIAM-Society for Industrial and Applied Mathematicsq, 2017
- Softcover
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Language: English
Published by SIAM - Society for Industrial and Applied Mathematics, 2017
- Softcover
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Condition: New. 2017. paperback. . . . . .

Language: English
Published by SIAM-Society for Industrial and Applied Mathematicsq, 2017
- Softcover
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Language: English
Published by SIAM-Society for Industrial and Applied Mathematicsq, 2017
- Softcover
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Language: English
Published by Society for Industrial and Applied Mathematics,U.S., US, 2017
- Softcover
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Paperback. Condition: New. The primary goal of this book is to provide a self-contained, comprehensive study of the main ?rst-order methods that are frequently used in solving large-scale problems. First-order methods exploit information on values and gradients/subgradients (but not Hessians) of the functions composing the model under consideration. With the increase in the number of applications that can be modeled as large or even huge-scale optimization problems, there has been a revived interest in using simple methods that require low iteration cost as well as low memory storage.The author has gathered, reorganized, and synthesized (in a unified manner) many results that are currently scattered throughout the literature, many of which cannot be typically found in optimization books.First-Order Methods in Optimization offers comprehensive study of first-order methods with the theoretical foundations; provides plentiful examples and illustrations; emphasizes rates of convergence and complexity analysis of the main first-order methods used to solve large-scale problems; and covers both variables and functional decomposition methods.…

Language: English
Published by SIAM-Society for Industrial and Applied Mathematicsq, 2017
- Softcover
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Language: English
Published by Society for Industrial & Applied Mathematics, 2017
- Softcover
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Condition: New. pp. 484.

Language: English
Published by SIAM - Society for Industrial and Applied Mathematics, 2017
- Softcover
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Language: English
Published by Society for Industrial & Applied Mathematics,U.S., 2017
- Softcover
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Paperback / softback. Condition: New. New copy - Usually dispatched within 4 working days.

Language: English
Published by Society for Industrial & Applied Mathematics, 2017
- Softcover
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Condition: New. pp. 484.

Language: English
Published by SIAM - Society for Industrial and Applied Mathematics, 2017
- Softcover
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Kartoniert / Broschiert. Condition: New. Provides a self-contained, comprehensive study of the main first-order methods that are frequently used in solving large-scale problems. The author has gathered, reorganized, and synthesized (in a unified manner) many results that are currently scattered th.

Language: English
Published by SIAM-Society for Industrial and Applied Mathematicsq, 2017
- Softcover
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Condition: New. In English.

Language: English
Published by Society For Industrial & Applied Mathematics,U.S. Nov 2017, 2017
- Softcover
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Taschenbuch. Condition: Neu. Neuware - Provides a self-contained, comprehensive study of the main first-order methods that are frequently used in solving large-scale problems. The author has gathered, reorganized, and synthesized (in a unified manner) many results that are currently scattered throughout the literature, many of which cannot be typically found in optimization books.…

Language: English
Published by Society for Industrial and Applied Mathematics,U.S., US, 2017
- Softcover
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Paperback. Condition: New. The primary goal of this book is to provide a self-contained, comprehensive study of the main ?rst-order methods that are frequently used in solving large-scale problems. First-order methods exploit information on values and gradients/subgradients (but not Hessians) of the functions composing the model under consideration. With the increase in the number of applications that can be modeled as large or even huge-scale optimization problems, there has been a revived interest in using simple methods that require low iteration cost as well as low memory storage.The author has gathered, reorganized, and synthesized (in a unified manner) many results that are currently scattered throughout the literature, many of which cannot be typically found in optimization books.First-Order Methods in Optimization offers comprehensive study of first-order methods with the theoretical foundations; provides plentiful examples and illustrations; emphasizes rates of convergence and complexity analysis of the main first-order methods used to solve large-scale problems; and covers both variables and functional decomposition methods.…