9783540689355 - advances in automatic differentiation (lecture notes in computational science and engineering, band 64) (4 Ergebnisse)

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Sprache: Englisch
Verlag: Springer, 2008
Serie: Lecture Notes in Computational Science and Engineering, Buch 41 von 111. Buch 41 von 111 - Lecture Notes in Computational Science and Engineering
- Softcover
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Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 388 | Sprache: Englisch | Produktart: Bücher | The Fifth International Conference on Automatic Differentiation held from August 11 to 15, 2008 in Bonn, Germany, is the most recent one in a series that began in Breckenridge, USA, in 1991 and continued in Santa Fe, USA, in 1996, Nice,… France, in 2000 and Chicago, USA, in 2004. The 31 papers included in these proceedings re?ect the state of the art in automatic differentiation (AD) with respect to theory, applications, and tool development. Overall, 53 authors from institutions in 9 countries contributed, demonstrating the worldwide acceptance of AD technology in computational science. Recently it was shown that the problem underlying AD is indeed NP-hard, f- mally proving the inherently challenging nature of this technology. So, most likely, no deterministic ¿silver bullet¿ polynomial algorithm can be devised that delivers optimum performance for general codes. In this context, the exploitation of doma- speci?c structural information is a driving issue in advancing practical AD tool and algorithm development. This trend is prominently re?ected in many of the pub- cations in this volume, not only in a better understanding of the interplay of AD and certain mathematical paradigms, but in particular in the use of hierarchical AD approaches that judiciously employ general AD techniques in application-speci?c - gorithmic harnesses. In this context, the understanding of structures such as sparsity of derivatives, or generalizations of this concept like scarcity, plays a critical role, in particular for higher derivative computations.
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Verlag: Springer, 2008
Serie: Lecture Notes in Computational Science and Engineering, Buch 41 von 111. Buch 41 von 111 - Lecture Notes in Computational Science and Engineering
- Softcover
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Taschenbuch. Zustand: Neu. Advances in Automatic Differentiation | Christian H. Bischof (u. a.) | Taschenbuch | Lecture Notes in Computational Science and Engineering | xviii | Englisch | 2008 | Springer | EAN 9783540689355 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[do…t]hartmann[at]springer[dot]com | Anbieter: preigu.

Sprache: Englisch
Verlag: Springer, Springer Spektrum, 2008
Serie: Lecture Notes in Computational Science and Engineering, Buch 41 von 111. Buch 41 von 111 - Lecture Notes in Computational Science and Engineering
- Softcover
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The Fifth International Conference on Automatic Differentiation held from August 11 to 15, 2008 in Bonn, Germany, is the most recent one in a series that began in Breckenridge, USA, in 1991 and continued in Santa Fe, USA, in 1996, Nice, France, in 20…00 and Chicago, USA, in 2004. The 31 papers included in these proceedings re ect the state of the art in automatic differentiation (AD) with respect to theory, applications, and tool development. Overall, 53 authors from institutions in 9 countries contributed, demonstrating the worldwide acceptance of AD technology in computational science. Recently it was shown that the problem underlying AD is indeed NP-hard, f- mally proving the inherently challenging nature of this technology. So, most likely, no deterministic 'silver bullet' polynomial algorithm can be devised that delivers optimum performance for general codes. In this context, the exploitation of doma- speci c structural information is a driving issue in advancing practical AD tool and algorithm development. This trend is prominently re ected in many of the pub- cations in this volume, not only in a better understanding of the interplay of AD and certain mathematical paradigms, but in particular in the use of hierarchical AD approaches that judiciously employ general AD techniques in application-speci c - gorithmic harnesses. In this context, the understanding of structures such as sparsity of derivatives, or generalizations of this concept like scarcity, plays a critical role, in particular for higher derivative computations.