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BioGD: Bio-inspired robust gradient descent
Recent research in machine learning pointed to the core problem of state-of-the-art models which impedes their widespread adoption in different domains. The models’ inability to differentiate between noise and subtle, yet significant variation in data leads to their vulnerability to adversarial pert...
Autores principales: | Kulikovskikh, Ilona, Prokhorov, Sergej, Lipić, Tomislav, Legović, Tarzan, Šmuc, Tomislav |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6611597/ https://www.ncbi.nlm.nih.gov/pubmed/31276469 http://dx.doi.org/10.1371/journal.pone.0219004 |
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