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Influence Function and Robust Variant of Kernel Canonical Correlation Analysis
Many unsupervised kernel methods rely on the estimation of kernel covariance operator (kernel CO) or kernel cross-covariance operator (kernel CCO). Both are sensitive to contaminated data, even when bounded positive definite kernels are used. To the best of our knowledge, there are few well-founded...
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| Published in: | Neurocomputing |
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| Main Authors: | , , |
| Format: | Artigo |
| Language: | Inglês |
| Published: |
2018
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| Subjects: | |
| Online Access: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6223640/ https://ncbi.nlm.nih.gov/pubmed/30416263 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.neucom.2018.04.008 |
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