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Convex Analysis and Minimization Algorithms II - Advanced Theory and Bundle Methods (Paperback, Softcover reprint of hardcover 1st ed. 1993) Loot Price: R2,152
Discovery Miles 21 520
You Save: R1,412 (40%)
Convex Analysis and Minimization Algorithms II - Advanced Theory and Bundle Methods (Paperback, Softcover reprint of hardcover...

Convex Analysis and Minimization Algorithms II - Advanced Theory and Bundle Methods (Paperback, Softcover reprint of hardcover 1st ed. 1993)

Jean-Baptiste Hiriart-Urruty, Claude Lemar echal

Series: Grundlehren der mathematischen Wissenschaften, 306

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List price R3,564 Loot Price R2,152 Discovery Miles 21 520 | Repayment Terms: R202 pm x 12* You Save R1,412 (40%)

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From the reviews: "The account is quite detailed and is written in a manner that will appeal to analysts and numerical practitioners alike...they contain everything from rigorous proofs to tables of numerical calculations.... one of the strong features of these books...that they are designed not for the expert, but for those who whish to learn the subject matter starting from little or no background...there are numerous examples, and counter-examples, to back up the theory...To my knowledge, no other authors have given such a clear geometric account of convex analysis." "This innovative text is well written, copiously illustrated, and accessible to a wide audience"

General

Imprint: Springer-Verlag
Country of origin: Germany
Series: Grundlehren der mathematischen Wissenschaften, 306
Release date: December 2010
First published: 1993
Authors: Jean-Baptiste Hiriart-Urruty • Claude Lemar echal
Dimensions: 235 x 155 x 37mm (L x W x T)
Format: Paperback
Pages: 348
Edition: Softcover reprint of hardcover 1st ed. 1993
ISBN-13: 978-3-642-08162-0
Categories: Books > Science & Mathematics > Mathematics > Numerical analysis
Books > Business & Economics > Business & management > Management & management techniques > Operational research
Books > Science & Mathematics > Mathematics > Calculus & mathematical analysis > Calculus of variations
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LSN: 3-642-08162-2
Barcode: 9783642081620

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