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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Detalles Bibliográficos
Autor principal: Li, Fanzhang (-)
Otros Autores: Zhang, Li, Zhang, Zhao
Formato: Libro electrónico
Idioma:Inglés
Publicado: Berlin ; Boston : Walter de Gruyter, GmbH 2018.
Colección:EBSCO Academic eBook Collection Complete.
Acceso en línea:Conectar con la versión electrónica
Ver en Universidad de Navarra:https://innopac.unav.es/record=b47421010*spi
Descripción
Sumario: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 artificial 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, artificial 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.
Descripción Física:1 recurso electrónico
Formato:Forma de acceso: World Wide Web.
Bibliografía:Incluye referencias bibliográficas e índice.
ISBN:9783110499506
9783110498073