American industry is becoming more aware of the importance of applying statistical methods to imp...

This book introduces finite difference methods for both ordinary differential equations (ODEs) an...

Sport and statistics collide in this collection of articles (from American Statistical Associatio...

The authors describe the first unified theory of polynomial-time interior-point methods. Their ap...

Features illustrations that use the Lorenz system, laser data, and natural language data. The con...

How do you select a winner from a field of candidates? How do you rank a field of candidates? How...

Developments in optimization theory, including emphasis on large problems and on interior-point m...

The Lanczos and conjugate gradient (CG) algorithms are fascinating numerical algorithms. This boo...

This book provides a unified and accessible introduction to the basic theory of finite difference...

Proceedings of the Eighteenth Annual Acm-Siam Symposium on Discrete Algorithms

Learning through doing is the foundation of this book, which allows readers to explore case studi...

This book serves well as an introduction into the more theoretical aspects of the use of spline m...

This book offers an introductory and intermediate-level treatment of all the essential ingredient...

Smart Material Systems describes several novel applications currently under investigation that ex...

This book provides a protocol for conducting gauge repeatability and reproducibility (R&R) experi...

A study of the art and science of solving elliptic problems numerically, with an emphasis on prob...

Chaos is a deterministic random phenomenon. Many signal processes (e.g., radar and sonar) have a ...

This textbook develops the use of probability and statistics in engineering reliability and maint...

Graphs are among the most important abstract data types in computer science, and the algorithms t...

Climate modeling and simulation teach us about past, present, and future conditions of life on ea...

Riemann–Hilbert problems are fundamental objects of study within complex analysis. Many problems ...

Discrete Convex Analysis provides the information that professionals in optimization will need to...

Personalized medicine is a medical paradigm that emphasizes systematic use of individual patient ...

This is the first book on parallel MATLAB and the first parallel computing book focused on the de...

Presents recent advances in the mathematical theory of discrete optimization, particularly those ...

Adapted from a series of lectures given by the authors, this monograph focuses on radial basis fu...

Functions of a complex variable are used to solve applications in various branches of mathematics...

This textbook grew out of a course that the highly respected applied mathematician Lee Segel taug...

This classic textbook provides a modern and complete guide to the calculation of eigenvalues of m...

Physics and Partial Differential Equations, Volume II proceeds directly from Volume I (SIAM, 2012...

In this much-expanded second edition, author Yair Shapira presents new applications and a substan...

This classic book provides a rigorous treatment of the Riesz–Fredholm theory of compact operators...

An accessible text for the study of numerical methods for solving least squares problems remains ...

Asymptotic methods are frequently used in many branches of both pure and applied mathematics, and...

This book describes state-of-the-art advances and applications of the unified transform and its r...

Diffusion has been used extensively in many scientific disciplines to model a wide variety of phe...

Like a pianist who practices from a book of études, readers of Programming Projects in C for Stud...

This textbook provides undergraduate students with an introduction to optimization and its uses f...

Mathematical Models in Biology is an introductory book for readers interested in biological appli...

LAPACK is a library of numerical linear algebra subroutines designed for high performance on work...

Exact and Approximate Modeling of Linear Systems: A Behavioral Approach elegantly introduces the ...

A comprehensive treatment of optimization problems involving uncertain parameters for which stoch...

This book addresses modern nonlinear programming (NLP) concepts and algorithms, especially as the...

The linear sampling method is the oldest and most developed of the qualitative methods in inverse...

Provides an introduction to the state of the art of the probability theory that is most directly ...

Shows both the shortcomings and benefits of each technique, and even demonstrates useful combinat...

Topics include: ways modern statistical procedures can yield estimates of pi more precisely than ...

Included in this volume are the Invited Talks given at the 5th International Congress of Industri...