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L0-norm Constrained Autoencoders for Unsupervised Outlier Detection
Unsupervised outlier detection is commonly performed using reconstruction-based methods such as Principal Component Analysis. A recent problem in this field is the learning of low-dimensional nonlinear manifolds under L0-norm constraints for error terms. Despite significant efforts, no method that c...
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| Publicado no: | Advances in Knowledge Discovery and Data Mining |
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| Main Authors: | , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7206274/ https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/978-3-030-47436-2_51 |
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