A Matrix Algebra Approach to Artificial Intelligence

Author: Xian-Da Zhang

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Description

Matrix algebra plays an important role in many core artificial intelligence (AI) areas, including machine learning, neural networks, support vector machines (SVMs) and evolutionary computation. This book offers a comprehensive and in-depth discussion of matrix algebra theory and methods for these four core areas of AI, while also approaching AI from a theoretical matrix algebra perspective. The book consists of two parts: the first discusses the fundamentals of matrix algebra in detail, while the second focuses on the applications of matrix algebra approaches in AI. Highlighting matrix algebra in graph-based learning and embedding, network embedding, convolutional neural networks and Pareto optimization theory, and discussing recent topics and advances, the book offers a valuable resource for scientists, engineers, and graduate students in various disciplines, including, but not limited to, computer science, mathematics and engineering. show more

Additional information

Weight 1602 g
Author

Xian-Da Zhang

Publisher

Springer Verlag, Singapore

Binding

Hardback

ISBN-10

9811527695

Dimensions

235 x 155

Language

English

Country of Pub

Singapore

Book Condition

New

Notes

389 Illustrations, black and white; XXXIV, 820 p. 389 illus.

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