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001			9783110499506
003			DE-B1597
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008			210830t20182019gw fo d z eng d
020			_a9783110499506
024	7		_a10.1515/9783110499506 _2doi
035			_a(DE-B1597)470633
035			_a(OCoLC)1066182573
040			_aDE-B1597 _beng _cDE-B1597 _erda
041	0		_aeng
044			_agw _cDE
072		7	_aCOM004000 _2bisacsh
100	1		_aLi, Fanzhang, _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _976883
245	1	0	_aLie Group Machine Learning / _cFanzhang Li, Li Zhang, Zhao Zhang.
264		1	_aBerlin ; _aBoston : _bDe Gruyter, _c[2018]
264		4	_c©2019
300			_a1 online resource (XVI, 517 p.)
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
505	0	0	_tFrontmatter -- _tPreface -- _tContents -- _t1. Lie group machine learning model -- _t2. Lie group subspace orbit generation learning -- _t3. Symplectic group learning -- _t4. Quantum group learning -- _t5. Lie group fibre bundle learning -- _t6. Lie group covering learning -- _t7. Lie group deep structure learning -- _t8. Lie group semi-supervised learning -- _t9. Lie group kernel learning -- _t10. Tensor learning -- _t11. Frame bundle connection learning -- _t12. Spectral estimation learning -- _t13. Finsler geometric learning -- _t14. Homology boundary learning -- _t15. Category representation learning -- _t16. Neuromorphic synergy learning -- _t17. Appendix -- _tAuthors -- _tIndex
506	0		_arestricted access _uhttp://purl.org/coar/access_right/c_16ec _fonline access with authorization _2star
520			_aThis 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			_aMode of access: Internet via World Wide Web.
546			_aIn English.
588	0		_aDescription based on online resource; title from PDF title page (publisher's Web site, viewed 30. Aug 2021)
650		7	_aCOMPUTERS / Intelligence (AI) & Semantics. _2bisacsh _976884
700	1		_aZhang, Li, _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _976885
700	1		_aZhang, Zhao, _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _976886
773	0	8	_iTitle is part of eBook package: _dDe Gruyter _tDG Plus eBook-Package 2019 _z9783110719567
773	0	8	_iTitle is part of eBook package: _dDe Gruyter _tEBOOK PACKAGE COMPLETE DG 2019 English _z9783110616859
773	0	8	_iTitle is part of eBook package: _dDe Gruyter _tEBOOK PACKAGE COMPLETE 2018 English _z9783110604252
773	0	8	_iTitle is part of eBook package: _dDe Gruyter _tEBOOK PACKAGE COMPLETE 2018 _z9783110603255 _oZDB-23-DGG
773	0	8	_iTitle is part of eBook package: _dDe Gruyter _tEBOOK PACKAGE Engineering, Computer Sciences 2018 _z9783110603118 _oZDB-23-DEI
776	0		_cEPUB _z9783110498073
776	0		_cprint _z9783110500684
856	4	0	_uhttps://doi.org/10.1515/9783110499506
856	4	0	_uhttps://www.degruyter.com/isbn/9783110499506
856	4	2	_3Cover _uhttps://www.degruyter.com/cover/covers/9783110499506.jpg
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