Fast Evaluation of Partial Derivatives and Interval Slopes

Fast Evaluation of Partial Derivatives and Interval Slopes For functions that share intermediate results, the computation of partial derivatives can be modeled by node condensation on graphs. In this case, mixed evaluation strategies can outperform either the backward or the forward mode of automatic differentiation. In this paper we present new algorithms and heuristics to find good evaluation strategies for partial derivatives. We show that these techniques not only apply for interval derivatives but also for interval slopes. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Reliable Computing Springer Journals

Fast Evaluation of Partial Derivatives and Interval Slopes

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Publisher
Kluwer Academic Publishers
Copyright
Copyright © 1997 by Kluwer Academic Publishers
Subject
Mathematics; Numeric Computing; Approximations and Expansions; Computational Mathematics and Numerical Analysis; Mathematical Modeling and Industrial Mathematics
ISSN
1385-3139
eISSN
1573-1340
D.O.I.
10.1023/A:1009970723383
Publisher site
See Article on Publisher Site

Abstract

For functions that share intermediate results, the computation of partial derivatives can be modeled by node condensation on graphs. In this case, mixed evaluation strategies can outperform either the backward or the forward mode of automatic differentiation. In this paper we present new algorithms and heuristics to find good evaluation strategies for partial derivatives. We show that these techniques not only apply for interval derivatives but also for interval slopes.

Journal

Reliable ComputingSpringer Journals

Published: Oct 14, 2004

References

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