Numerical Algorithms: Methods for Computer Vision, Machine Learning, and Graphics
by Justin Solomon
Publisher: CRC Press 2015
Number of pages: 397
This book presents a new approach to numerical analysis for modern computer scientists. Using examples from a broad base of computational tasks, including data processing, computational photography, and animation, the textbook introduces numerical modeling and algorithmic design from a practical standpoint and provides insight into the theoretical tools needed to support these skills.
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by Victor Shoup - Cambridge University Press
This introductory book emphasises algorithms and applications, such as cryptography and error correcting codes. It is accessible to a broad audience. Prerequisites are a typical undergraduate course in calculus and some experience in doing proofs.
by S. Basu, R. Pollack, M. Roy - Springer
The monograph gives a detailed exposition of the algorithmic real algebraic geometry. It is well written and will be useful both for beginners and for advanced readers, who work in real algebraic geometry or apply its methods in other fields.
by R. L. Constable, at al. - Prentice Hall
The authors offer a tutorial on the new mathematical ideas which underlie their research. Many of the ideas in this book will be accessible to a well-trained undergraduate with a good background in mathematics and computer science.
by Leonard Soicher, Franco Vivaldi - Queen Mary University of London
This text is a course in mathematical algorithms, intended for second year mathematics students. It introduces the algorithms for computing with integers, polynomials and vector spaces. The course requires no computing experience.