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Adversarial concept drift detection under poisoning attacks for robust data stream mining
Continuous learning from streaming data is among the most challenging topics in the contemporary machine learning. In this domain, learning algorithms must not only be able to handle massive volume of rapidly arriving data, but also adapt themselves to potential emerging changes. The phenomenon of e...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Springer US
2022
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9162121/ https://www.ncbi.nlm.nih.gov/pubmed/35668720 http://dx.doi.org/10.1007/s10994-022-06177-w |