Concentration Bounds for High Sensitivity Functions Through Differential Privacy
A new line of work demonstrates how differential privacy can be used as a mathematical tool for guaranteeing generalization in adaptive data analysis. Specifically, if a differentially private analysis is applied on a sample S of i.i.d. examples to select a low-sensitivity function f, then w.h.p. f...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Labor Dynamics Institute
2019-03-01
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| Series: | The Journal of Privacy and Confidentiality |
| Subjects: | |
| Online Access: | https://journalprivacyconfidentiality.org/index.php/jpc/article/view/658 |