Faster First-Order Methods for Stochastic Non-Convex Optimization on Riemannian Manifolds

First-order non-convex Riemannian optimization algorithms have gained recent popularity in structured machine learning problems including principal component analysis and low-rank matrix completion. The current paper presents an efficient Riemannian Stochastic Path Integrated Differential EstimatoR...

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Veröffentlicht in:	IEEE transactions on pattern analysis and machine intelligence. - 1979. - 43(2021), 2 vom: 26. Feb., Seite 459-472
1. Verfasser:	Zhou, Pan (VerfasserIn)
Weitere Verfasser:	Yuan, Xiao-Tong, Yan, Shuicheng, Feng, Jiashi
Format:	Online-Aufsatz
Sprache:	English
Veröffentlicht:	2021
Zugriff auf das übergeordnete Werk:	IEEE transactions on pattern analysis and machine intelligence
Schlagworte:	Journal Article