• Title: Linear Algebra and Optimization with Applications to Machine Learning
• Author(s) Jean Gallier and Jocelyn Quaintance
• Publisher: World Scientific Pub Co Inc (2020); eBook (University of Pennsylvania, 2025)
• Paperback: 877 pages
• eBook: PDF
• Language: English
• ISBN-10/ASIN: 9811216568
• ISBN-13: 978-9811216565
Jean Gallier J. Quaintance
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Book Description

This book applies the linear algebra concepts to optimization problems which frequently occur throughout machine learning. Highlights include careful derivations and applications of the simplex algorithm, the dual-simplex algorithm, and the primal-dual algorithm.

• Jean Gallier is a researcher in computational logic at the University of Pennsylvania, where he holds appointments in the Computer and Information Science Department and the Department of Mathematics.

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• Linear Algebra, Matrix Algebra, and Linear Systems
• Machine Learning
• Optimization Problems

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