Differential Privacy for Regularised Linear Regression-Reference-Cited by-同舟云学术

Differential Privacy for Regularised Linear Regression

Published:2018 Issue: Volume: Page:483-491
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
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Author:

Dandekar Ashish,Basu Debabrota,Bressan Stéphane

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-98812-2_44

Reference18 articles.

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2. Dandekar, A., Basu, D., Bressan, S.: Differential privacy for regularised linear regression. Technical report TRA6/18, National University of Singapore, June 2018. https://dl.comp.nus.edu.sg/handle/1900.100/7051

3. Diamond, S., Boyd, S.: CVXPY: a Python-embedded modeling language for convex optimization. J. Mach. Learn. Res. 17(83), 1–5 (2016)

4. Lecture Notes in Computer Science;C Dwork,2006

5. Dwork, C., Roth, A., et al.: The algorithmic foundations of differential privacy. Found. Trends$${\textregistered }$$ Theoret. Comput. Sci. 9(3–4), 211–407 (2014)

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