Evaluating Derivatives: Principles and Techniques of Algorithmic Differentiation, Second Edition

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SIAM, Jan 1, 2008 - Mathematics - 459 pages
This title is a comprehensive treatment of algorithmic, or automatic, differentiation. The second edition covers recent developments in applications and theory, including an elegant NP completeness argument and an introduction to scarcity.
 

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Contents

Introduction
1
A Framework for Evaluating Functions
15
Fundamentals of Forward and Reverse
31
Memory Issues and Complexity Bounds
61
Repeating and Extending Reverse
91
Implementation and Software
107
Sparse Forward and Reverse
145
Exploiting Sparsity by Compression
161
Jacobian and Hessian Accumulation
211
Observations on Efficiency
245
Reversal Schedules and Checkpointing
261
Taylor and Tensor Coefficients
299
Differentiation without Differentiability
335
Implicit and Iterative Differentiation
367
Epilogue
397
Copyright

Going beyond Forward and Reverse
185

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