Kernel dependence analysis and graph structure morphing for novelty detection with high-dimensional small size data set
In this study, we propose a new approach for novelty detection that uses kernel dependence techniques for characterizing the statistical dependencies of random variables (RV) and use this characterization as a basis for making inference. Considering the statistical dependencies of the RVs in multiva...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Elsevier BV
2020
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| Online Access: | https://hdl.handle.net/1721.1/126504 |