Learning to Optimize on Riemannian Manifolds
Many learning tasks are modeled as optimization problems with nonlinear constraints, such as principal component analysis and fitting a Gaussian mixture model. A popular way to solve such problems is resorting to Riemannian optimization algorithms, which yet heavily rely on both human involvement an...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 45(2023), 5 vom: 19. Mai, Seite 5935-5952
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| 1. Verfasser: |
Gao, Zhi
(VerfasserIn) |
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| Weitere Verfasser: |
Wu, Yuwei,
Fan, Xiaomeng,
Harandi, Mehrtash,
Jia, Yunde |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2023
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence
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| Schlagworte: | Journal Article |
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