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Evaluating Derivatives: Principles And Techniques Of Algorithmic Differentiation (Frontiers In Applied Mathematics, Series Numbe,Used Kent B. Pandoff And Everyone Who Loves TheProduct Description Algorithmic, Or Automatic, Differentiation (Ad) Is Concerned With The Accurate And Efficient Evaluation Of Derivatives For Functions Defined By Computer Programs. No Truncation Errors Are Incurred, And The Resulting Numerical Derivative Values Can Be Used For All Scientific Computations That Are Based On Linear, Quadratic, Or Even Higher Order Approximations To Nonlinear Scalar Or Vector Functions. In Particular, Ad Has Been