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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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This collection covers advances in automatic differentiation theory and practice. Computer scientists and mathematicians will learn about recent developments in automatic differentiation theory as well as mechanisms for the construction of robust and powerful automatic differentiation tools. Computational scientists and engineers will benefit from the discussion of various applications, which provide insight into effective strategies for using automatic differentiation for inverse problems and design optimization.
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- EditorialSpringer
- Año de publicación2008
- ISBN 10 3540689354
- ISBN 13 9783540689355
- EncuadernaciónTapa blanda
- IdiomaInglés
- Número de páginas386
- EditorBischof Christian H., Bücker H. Martin, Hovland Paul, Naumann Uwe, Utke Jean
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Advances in Automatic Differentiation
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Springer Berlin Heidelberg, 2008
ISBN 10: 3540689354
ISBN 13: 9783540689355
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Advances in Automatic Differentiation (Lecture Notes in Computational Science and Engineering, 64)
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Advances in Automatic Differentiation
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Advances in Automatic Differentiation
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 388 pp. Englisch. Nº de ref. del artículo: 9783540689355
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Advances in Automatic Differentiation (Lecture Notes in Computational Science and Engineering, 64)
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Advances in Automatic Differentiation
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ISBN 10: 3540689354
ISBN 13: 9783540689355
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Taschenbuch. Condición: 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 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. Nº de ref. del artículo: 9783540689355
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