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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...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Berlin ; Boston :
Walter de Gruyter, GmbH,
2018.
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| Temas: | |
| Acceso en línea: | Texto completo |
MARC
| LEADER | 00000cam a2200000 i 4500 | ||
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| 001 | EBSCO_on1066182573 | ||
| 003 | OCoLC | ||
| 005 | 20231017213018.0 | ||
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| 049 | |a UAMI | ||
| 100 | 1 | |a Li, Fanzhang, |e author. | |
| 245 | 1 | 0 | |a Lie group machine learning / |c Li Fanzhang, Zhang Li, Zhang Zhao. |
| 264 | 1 | |a Berlin ; |a Boston : |b Walter de Gruyter, GmbH, |c 2018. | |
| 264 | 4 | |c ©2019 | |
| 300 | |a 1 online resource (xvi, 517 pages) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 504 | |a Includes bibliographical references and index. | ||
| 588 | 0 | |a Online resource; title from digital title page (De Gruyter, viewed July 17, 2020). | |
| 520 | |a 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. | ||
| 505 | 0 | |a Lie group machine learning model -- Lie group subspace orbit generation learning -- Symplectic group learning -- Quantum group learning -- Lie group fibre bundle learning -- Lie group covering learning -- Lie group deep structure learning -- Lie group semi-supervised learning -- Lie group kernel learning -- Tensor learning -- Frame bundle connection learning -- Spectral estimation learning -- Finsler geometric learning -- Homology boundary learning -- Category representation learning -- Neuromorphic synergy learning. | |
| 545 | |a Li Zhang (M’08) received the degree of B.Sc. in1997 and the degree of Ph.D. in 2002 in electronic engineering from Xidian University, Xi’an, China. She is now a professor at the School of Computer Science and Technology, Soochow University, Suzhou, China. | ||
| 546 | |a In English. | ||
| 590 | |a eBooks on EBSCOhost |b EBSCO eBook Subscription Academic Collection - Worldwide | ||
| 650 | 0 | |a Machine learning. | |
| 650 | 0 | |a Lie groups. | |
| 650 | 6 | |a Apprentissage automatique. | |
| 650 | 6 | |a Groupes de Lie. | |
| 650 | 7 | |a COMPUTERS |x General. |2 bisacsh | |
| 650 | 7 | |a Lie groups. |2 fast |0 (OCoLC)fst00998135 | |
| 650 | 7 | |a Machine learning. |2 fast |0 (OCoLC)fst01004795 | |
| 700 | 1 | |a Zhang, Li, |e author. |u School of Computer Science and Technology, Soochow University, China | |
| 700 | 1 | |a Zhang, Zhao |c (Computer scientist), |e author. | |
| 776 | 0 | 8 | |i Print version: |a Li, Fanzhang. |t Lie group machine learning. |d Berlin ; Boston : Walter de Gruyter, GmbH, [2019] |z 9783110500684 |w (DLC) 2018951019 |w (OCoLC)1044854219 |
| 856 | 4 | 0 | |u https://ebsco.uam.elogim.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1927020 |z Texto completo |
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