### About this book

In 1984, N. Karmarkar published a seminal paper on algorithmic linear
programming. During the subsequent decade, it stimulated a huge outpouring of
new algorithmic results by researchers world-wide in many areas of
mathematical programming and numerical computation. This book gives an
overview of the resulting, dramatic reorganization that has occurred in one of
these areas: algorithmic differentiable optimization and equation-solving, or,
more simply, algorithmic differentiable programming. The book is aimed at
readers familiar with advanced calculus, numerical analysis, in particular
numerical linear algebra, the theory and algorithms of linear and nonlinear
programming, and the fundamentals of computer science, in particular, computer
programming and the basic models of computation and complexity theory. J.L.
Nazareth is a Professor in the Department of Pure and Applied Mathematics at
Washington State University. He is the author of two books previously
published by Springer-Verlag, DLP and Extensions: An Optimization Model and
Decision Support System (2001) and The Newton-Cauchy Framework: A Unified
Approach to Unconstrained Nonlinear Minimization (1994).
Written for:

Researchers in optimization, graduate mathematics students