Lie Group Machine Learning / / Fanzhang Li, Li Zhang, Zhao Zhang.
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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Superior document: | Title is part of eBook package: De Gruyter DG Plus eBook-Package 2019 |
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Place / Publishing House: | Berlin ;, Boston : : De Gruyter, , [2018] ©2019 |
Year of Publication: | 2018 |
Language: | English |
Online Access: | |
Physical Description: | 1 online resource (XVI, 517 p.) |
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LEADER | 05353nam a22007335i 4500 | ||
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001 | 9783110499506 | ||
003 | DE-B1597 | ||
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020 | |a 9783110499506 | ||
024 | 7 | |a 10.1515/9783110499506 |2 doi | |
035 | |a (DE-B1597)470633 | ||
035 | |a (OCoLC)1066182573 | ||
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072 | 7 | |a COM004000 |2 bisacsh | |
100 | 1 | |a Li, Fanzhang, |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
245 | 1 | 0 | |a Lie Group Machine Learning / |c Fanzhang Li, Li Zhang, Zhao Zhang. |
264 | 1 | |a Berlin ; |a Boston : |b De Gruyter, |c [2018] | |
264 | 4 | |c ©2019 | |
300 | |a 1 online resource (XVI, 517 p.) | ||
336 | |a text |b txt |2 rdacontent | ||
337 | |a computer |b c |2 rdamedia | ||
338 | |a online resource |b cr |2 rdacarrier | ||
347 | |a text file |b PDF |2 rda | ||
505 | 0 | 0 | |t Frontmatter -- |t Preface -- |t Contents -- |t 1. Lie group machine learning model -- |t 2. Lie group subspace orbit generation learning -- |t 3. Symplectic group learning -- |t 4. Quantum group learning -- |t 5. Lie group fibre bundle learning -- |t 6. Lie group covering learning -- |t 7. Lie group deep structure learning -- |t 8. Lie group semi–supervised learning -- |t 9. Lie group kernel learning -- |t 10. Tensor learning -- |t 11. Frame bundle connection learning -- |t 12. Spectral estimation learning -- |t 13. Finsler geometric learning -- |t 14. Homology boundary learning -- |t 15. Category representation learning -- |t 16. Neuromorphic synergy learning -- |t 17. Appendix -- |t Authors -- |t Index |
506 | 0 | |a restricted access |u http://purl.org/coar/access_right/c_16ec |f online access with authorization |2 star | |
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 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. Li Fanzhang is professor at the Soochow University, China. He is director of network security engineering laboratory in Jiangsu Province and is also the director of the Soochow Institute of industrial large data. He published more than 200 papers, 7 academic monographs, and 4 textbooks. Zhang Li is professor at the School of Computer Science and Technology of the Soochow University. She published more than 100 papers in journals and conferences, and holds 23 patents. Zhang Zhao is currently an associate professor at the School of Computer Science and Technology of the Soochow University. He has authored and co-authored more than 60 technical papers. | ||
538 | |a Mode of access: Internet via World Wide Web. | ||
546 | |a In English. | ||
588 | 0 | |a Description based on online resource; title from PDF title page (publisher's Web site, viewed 30. Aug 2021) | |
650 | 7 | |a COMPUTERS / Intelligence (AI) & Semantics. |2 bisacsh | |
700 | 1 | |a Zhang, Li, |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
700 | 1 | |a Zhang, Zhao, |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
773 | 0 | 8 | |i Title is part of eBook package: |d De Gruyter |t DG Plus eBook-Package 2019 |z 9783110719567 |
773 | 0 | 8 | |i Title is part of eBook package: |d De Gruyter |t EBOOK PACKAGE COMPLETE DG 2019 English |z 9783110616859 |
773 | 0 | 8 | |i Title is part of eBook package: |d De Gruyter |t EBOOK PACKAGE COMPLETE 2018 English |z 9783110604252 |
773 | 0 | 8 | |i Title is part of eBook package: |d De Gruyter |t EBOOK PACKAGE COMPLETE 2018 |z 9783110603255 |o ZDB-23-DGG |
773 | 0 | 8 | |i Title is part of eBook package: |d De Gruyter |t EBOOK PACKAGE Engineering, Computer Sciences 2018 |z 9783110603118 |o ZDB-23-DEI |
776 | 0 | |c EPUB |z 9783110498073 | |
776 | 0 | |c print |z 9783110500684 | |
856 | 4 | 0 | |u https://doi.org/10.1515/9783110499506 |
856 | 4 | 0 | |u https://www.degruyter.com/isbn/9783110499506 |
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