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Numerical Algorithms
Methods for Computer Vision, Machine Learning, and Graphics
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Format: Hardback
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Book Hero Magic created this recommendation. While it's new and still learning, it may not be perfect - your feedback is welcome! IS THIS YOUR NEXT READ?
Ideal for advanced undergraduates and beginning graduate students in computer science and related fields, especially those with experience in calculus and linear algebra. The book also supports readers with discrete mathematics backgrounds by providing relevant continuous mathematics reminders.
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Book Hero Magic formatted this description to make it easier to read. While it's new and
still learning, it may not be perfect - your
feedback is welcome!
Description
Numerical Algorithms: Methods for Computer Vision, Machine Learning, and Graphics 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.
The book covers a wide range of topics—from numerical linear algebra to optimization and differential equations—focusing on real-world motivation and unifying themes. It incorporates cases from computer science research and practice, accompanied by highlights from in-depth literature on each subtopic. Comprehensive end-of-chapter exercises encourage critical thinking and build students’ intuition while introducing extensions of the basic material.
The text is designed for advanced undergraduate and beginning graduate students in computer science and related fields with experience in calculus and linear algebra. For students with a background in discrete mathematics, the book includes some reminders of relevant continuous mathematical background.
Book Details
INFORMATION
ISBN: 9781482251883
Publisher: Apple Academic Press Inc.
Format: Hardback
Date Published: 13 July 2015
Country: Canada
Imprint: Apple Academic Press Inc.
Illustration: 14 Tables, black and white; 132 Illustrations, black and white
Audience: General / adult, Tertiary education
DIMENSIONS
Width: 178.0mm
Height: 254.0mm
Weight: 880g
Pages: 400
About the Author
Justin Solomon is an assistant professor in the Department of Electrical Engineering and Computer Science at MIT, where he studies problems in shape analysis, machine learning, and graphics from a geometric perspective. He received a PhD in computer science from Stanford University, where he was also a lecturer for courses in graphics, differential geometry, and numerical methods. Subsequently he served as an NSF Mathematical Sciences Postdoctoral Fellow at Princeton’s Program in Applied and Computational Mathematics. Before his graduate studies, he was a member of Pixar’s Tools Research group.
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