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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...
Autores principales: | Ishii, Yoshinao, Koide, Satoshi, Hayakawa, Keiichiro |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7206274/ http://dx.doi.org/10.1007/978-3-030-47436-2_51 |
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