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Supporting Regularized Logistic Regression Privately and Efficiently
As one of the most popular statistical and machine learning models, logistic regression with regularization has found wide adoption in biomedicine, social sciences, information technology, and so on. These domains often involve data of human subjects that are contingent upon strict privacy regulatio...
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| Publicado en: | PLoS One |
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| Autores principales: | , , , |
| Formato: | Artigo |
| Lenguaje: | Inglês |
| Publicado: |
Public Library of Science
2016
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| Materias: | |
| Acceso en línea: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4894560/ https://ncbi.nlm.nih.gov/pubmed/27271738 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0156479 |
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