Lie Group Machine Learning

This book explains deep learning concepts and derives semi-supervised learning and nuclear learning frameworks based on cognition mechanism and Lie group theory. Lie group machine learning is a theoretical basis for brain intelligence, Neuromorphic learning (NL), advanced machine learning, and advan...

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Bibliographic Details
Main Author: Fanzhang, Li
Other Authors: Li, Zhang, Zhao, Zhang
Format: eBook
Language:English
Published: Berlin ; Boston De Gruyter 2019
Subjects:
Online Access:
Collection: DeGruyter MPG Collection - Collection details see MPG.ReNa
Description
Summary:This book explains deep learning concepts and derives semi-supervised learning and nuclear learning frameworks based on cognition mechanism and Lie group theory. Lie group machine learning is a theoretical basis for brain intelligence, Neuromorphic learning (NL), advanced machine learning, and advanced artifi cial intelligence. The book further discusses algorithms and applications in tensor learning, spectrum estimation learning, Finsler geometry learning, Homology boundary learning, and prototype theory. With abundant case studies, this book can be used as a reference book for senior college students and graduate students as well as college teachers and scientific and technical personnel involved in computer science, artifi cial intelligence, machine learning, automation, mathematics, management science, cognitive science, financial management, and data analysis. In addition, this text can be used as the basis for teaching the principles of machine learning.
Physical Description:XVI, 517 Seiten
ISBN:978-3-11-049807-3
978-3-11-049950-6