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Lie group machine learning / / Li Fanzhang, Zhang Li, Zhang Zhao
| Lie group machine learning / / Li Fanzhang, Zhang Li, Zhang Zhao |
| Autore | Li Fanzhang |
| Pubbl/distr/stampa | Berlin ; ; Boston : , : De Gruyter, , [2019] |
| Descrizione fisica | 1 online resource (534 pages) |
| Disciplina | 006.31 |
| Soggetto topico |
Machine learning
Lie groups |
| Soggetto genere / forma | Electronic books. |
| ISBN |
3-11-049950-9
3-11-049807-3 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Frontmatter -- Preface -- Contents -- 1. Lie group machine learning model -- 2. Lie group subspace orbit generation learning -- 3. Symplectic group learning -- 4. Quantum group learning -- 5. Lie group fibre bundle learning -- 6. Lie group covering learning -- 7. Lie group deep structure learning -- 8. Lie group semi-supervised learning -- 9. Lie group kernel learning -- 10. Tensor learning -- 11. Frame bundle connection learning -- 12. Spectral estimation learning -- 13. Finsler geometric learning -- 14. Homology boundary learning -- 15. Category representation learning -- 16. Neuromorphic synergy learning -- 17. Appendix -- Authors -- Index |
| Record Nr. | UNINA-9910466375903321 |
Li Fanzhang
|
||
| Berlin ; ; Boston : , : De Gruyter, , [2019] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Lie group machine learning / / Li Fanzhang, Zhang Li, Zhang Zhao
| Lie group machine learning / / Li Fanzhang, Zhang Li, Zhang Zhao |
| Autore | Li Fanzhang |
| Pubbl/distr/stampa | Berlin ; ; Boston : , : De Gruyter, , [2019] |
| Descrizione fisica | 1 online resource (534 pages) |
| Disciplina | 006.31 |
| Soggetto topico |
Machine learning
Lie groups |
| ISBN |
3-11-049950-9
3-11-049807-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Frontmatter -- Preface -- Contents -- 1. Lie group machine learning model -- 2. Lie group subspace orbit generation learning -- 3. Symplectic group learning -- 4. Quantum group learning -- 5. Lie group fibre bundle learning -- 6. Lie group covering learning -- 7. Lie group deep structure learning -- 8. Lie group semi-supervised learning -- 9. Lie group kernel learning -- 10. Tensor learning -- 11. Frame bundle connection learning -- 12. Spectral estimation learning -- 13. Finsler geometric learning -- 14. Homology boundary learning -- 15. Category representation learning -- 16. Neuromorphic synergy learning -- 17. Appendix -- Authors -- Index |
| Record Nr. | UNINA-9910793294503321 |
|
Li Fanzhang
|
||
| Berlin ; ; Boston : , : De Gruyter, , [2019] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Lie group machine learning / / Li Fanzhang, Zhang Li, Zhang Zhao
| Lie group machine learning / / Li Fanzhang, Zhang Li, Zhang Zhao |
| Autore | Li Fanzhang |
| Pubbl/distr/stampa | Berlin ; ; Boston : , : De Gruyter, , [2019] |
| Descrizione fisica | 1 online resource (534 pages) |
| Disciplina | 006.31 |
| Soggetto topico |
Machine learning
Lie groups |
| ISBN |
3-11-049950-9
3-11-049807-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Frontmatter -- Preface -- Contents -- 1. Lie group machine learning model -- 2. Lie group subspace orbit generation learning -- 3. Symplectic group learning -- 4. Quantum group learning -- 5. Lie group fibre bundle learning -- 6. Lie group covering learning -- 7. Lie group deep structure learning -- 8. Lie group semi-supervised learning -- 9. Lie group kernel learning -- 10. Tensor learning -- 11. Frame bundle connection learning -- 12. Spectral estimation learning -- 13. Finsler geometric learning -- 14. Homology boundary learning -- 15. Category representation learning -- 16. Neuromorphic synergy learning -- 17. Appendix -- Authors -- Index |
| Record Nr. | UNINA-9910817957003321 |
|
Li Fanzhang
|
||
| Berlin ; ; Boston : , : De Gruyter, , [2019] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||