A differentially private kernel two-sample test
Kernel two-sample testing is a useful statistical tool in determining whether data samples arise from different distributions without imposing any parametric assumptions on those distributions. However, raw data samples can expose sensitive information about individuals who participate in scientific...
| Auteurs principaux: | , , , |
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| Format: | Conference item |
| Langue: | English |
| Publié: |
Springer Nature
2020
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