Random Features for Kernel Approximation : A Survey on Algorithms, Theory, and Beyond
The class of random features is one of the most popular techniques to speed up kernel methods in large-scale problems. Related works have been recognized by the NeurIPS Test-of-Time award in 2017 and the ICML Best Paper Finalist in 2019. The body of work on random features has grown rapidly, and hen...
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 44(2022), 10 vom: 26. Okt., Seite 7128-7148 |
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| Format: | Online-Aufsatz |
| Sprache: | English |
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2022
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence |
| Schlagworte: | Journal Article |
| Online verfügbar |
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