Outlier Detection for Robust Multi-Dimensional Scaling
Multi-dimensional scaling (MDS) plays a central role in data-exploration, dimensionality reduction and visualization. State-of-the-art MDS algorithms are not robust to outliers, yielding significant errors in the embedding even when only a handful of outliers are present. In this paper, we introduce...
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 41(2019), 9 vom: 27. Sept., Seite 2273-2279 |
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| Format: | Online-Aufsatz |
| Sprache: | English |
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2019
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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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