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Titlebook: Advances in Automatic Differentiation; Christian H. Bischof,H. Martin Bücker,Jean Utke Conference proceedings 2008 Springer-Verlag Berlin

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發(fā)表于 2025-3-21 17:37:29 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱Advances in Automatic Differentiation
影響因子2023Christian H. Bischof,H. Martin Bücker,Jean Utke
視頻videohttp://file.papertrans.cn/147/146817/146817.mp4
發(fā)行地址Includes supplementary material:
學科分類Lecture Notes in Computational Science and Engineering
圖書封面Titlebook: Advances in Automatic Differentiation;  Christian H. Bischof,H. Martin Bücker,Jean Utke Conference proceedings 2008 Springer-Verlag Berlin
影響因子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,
Pindex Conference proceedings 2008
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https://doi.org/10.1057/9781137316424ting schemes at the level of call trees. For a given amount of persistent memory the objective is to store selected arguments and/or results of subroutine calls such that the overall computational effort (the total number of floating-point operations performed by potentially repeated forward evaluat
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https://doi.org/10.1057/9781137316424that computes the function’s derivatives. To ensure the correctness of the AD transformed code, particularly for safety critical applications, we propose using the proof-carrying code paradigm: an AD tool must provide a machine checkable certificate for an AD generated code, which can be checked in
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https://doi.org/10.1007/978-3-030-77950-4 include parametric optimization, saddle point problems, Benders decompositions, and multilevel optimization. In this paper we adapt a known automatic differentiation (AD) technique for obtaining derivatives of implicitly defined functions for application to optimal value functions. The formulation
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Britain‘s Internees in the Second World War by a graph with a minimal edge count. So far, scarsity has been recognized only from a high-level application point of view, and no automatic exploitation has been attempted. We introduce an approach to recognize and use scarsity in computational graphs in a source transformation context. The goal
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