Efficient Low-Rank Semidefinite Programming With Robust Loss Functions

In real-world applications, it is important for machine learning algorithms to be robust against data outliers or corruptions. In this paper, we focus on improving the robustness of a large class of learning algorithms that are formulated as low-rank semi-definite programming (SDP) problems. Traditi...

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Veröffentlicht in:	IEEE transactions on pattern analysis and machine intelligence. - 1979. - 44(2022), 10 vom: 01. Okt., Seite 6153-6168
1. Verfasser:	Yao, Quanming (VerfasserIn)
Weitere Verfasser:	Yang, Hansi, Hu, En-Liang, Kwok, James T
Format:	Online-Aufsatz
Sprache:	English
Veröffentlicht:	2022
Zugriff auf das übergeordnete Werk:	IEEE transactions on pattern analysis and machine intelligence
Schlagworte:	Journal Article