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...
| Publié dans: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 41(2019), 9 vom: 27. Sept., Seite 2273-2279 |
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| Format: | Article en ligne |
| Langue: | English |
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2019
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| Accès à la collection: | IEEE transactions on pattern analysis and machine intelligence |
| Sujets: | Journal Article |
| Accès en ligne |
Volltext |