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Evaluating Derivatives: Principles and Techniques of Algorithmic Differentiation - Brossura

Griewank, Andreas

 
9780898714517: Evaluating Derivatives: Principles and Techniques of Algorithmic Differentiation

Sinossi

Covers the fundamentals of AD and its software, methods for sparse problems, higher derivatives, nonsmooth problems, and program reversal schedules.

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Descrizione del libro

The book is divided into three parts: a stand-alone introduction to the fundamentals of AD and its software, a thorough treatment of methods for sparse problems, and final chapters on higher derivatives, nonsmooth problems, and program reversal schedules.

Contenuti

Preface; Prologue; Introduction; Part I. Tangents and Gradients. A Framework for Evaluating Functions; Fundamentals of Forward and Reverse; Repeating and Extending Reverse; Implementation and Software; Part II. Jacobians and Hessians. Sparse Forward and Reverse; Exploiting Sparsity by Compression; Going Beyond Forward and Reverse; Observations on Efficiency; Part III. Advances and Reversals. Taylor and Tensor Coefficients; Differentiation without Differentiability; Serial and Parallel Reversal Schedules; Bibliography; Index.

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