Numerical Algorithms: Methods for Computer Vision, Machine Learning, and Graphics (Justin Solomon)

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Numerical Algorithms: Methods for Computer Vision, Machine Learning, and Graphics (Justin Solomon)

This book offers contemporary computer scientists a novel method of numerical analysis. The book presents numerical modeling and algorithmic design from a practical perspective and gives insight into the theoretical tools required to support these skills by using examples from a wide range of computational tasks, such as data processing, computational photography, and animation.

The book focuses on real-world inspiration and overarching themes while covering a broad range of topics, including numerical linear algebra, optimization, and differential equations. Highlights from the extensive literature on each subtopic are included together with cases from computer science research and application. Comprehensive end-of-chapter tasks introduce extensions of the fundamental subject while encouraging critical thinking and developing students' intuition.

With knowledge in calculus and linear algebra, the text is intended for advanced undergraduate and beginning graduate students studying computer science and related subjects. There are some reminders of pertinent continuous mathematical background in the text for students with a background in discrete mathematics.

Ebook Details

About the Authors
As an NSF Mathematical Sciences Postdoctoral Fellow at Princeton University's Program in Applied and Computational Mathematics, Justin Solomon is investigating geometrically-based issues in shape analysis, machine learning, and graphics. 
Published Date / Year
Har/Psc edition (July 13, 2015)
400 pages
eBook Format

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