Error Analysis and Variable Selection for Differential Private Learning Algorithm - Journal of Applied Mathematics and Physics

JAMP > Vol.5 No.4, April 2017

Journal of Applied Mathematics and Physics

Volume 5, Issue 4 (April 2017)

ISSN Print: 2327-4352 ISSN Online: 2327-4379

Google-based Impact Factor: 0.70 Citations

Error Analysis and Variable Selection for Differential Private Learning Algorithm ()

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DOI: 10.4236/jamp.2017.54079 1,035 Downloads 1,644 Views Citations

Author(s)

Weilin Nie, Cheng Wang

Affiliation(s)

Huizhou University, Huizhou, China.

ABSTRACT

In this paper, we construct a modified least squares regression algorithm which can provide privacy protection. A new concentration inequality is applied and the expected error bound is derived by error decomposition. Furthermore, via the error analysis, we find a method to choose an appropriate parameter to balance the error and privacy.

KEYWORDS

Differential Privacy, Least Squares Regularization, Concentration Inequality, Error Decomposition

Share and Cite:

Nie, W. and Wang, C. (2017) Error Analysis and Variable Selection for Differential Private Learning Algorithm. Journal of Applied Mathematics and Physics, 5, 900-911. doi: 10.4236/jamp.2017.54079.

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