A Matrix Algebra Approach to Artificial Intelligence
Publication year: 2020
ISBN: 978-981-15-2770-8
Internet Resource: Please Login to download book
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
Subject: Computer Science, Matrix Algebra, Artificial Intelligence, Linear Algebra, Machine Learning, Neural Networks, Evolutionary Computation, Learning Systems, Learning Algorithms, Support Vector Machine
