Dwork, C., Feldman, V., Hardt, M., Pitassi, T., Reingold, O. and Roth, A. (2015) Preserving Statistical Validity in Adaptive Data Analysis. ACM Symposium on the Theory of Computing, Portland, 14-17 June 2015, 117-126.
https://doi.org/10.1145/2746539.2746580

has been cited by the following article:

• TITLE: Error Analysis and Variable Selection for Differential Private Learning Algorithm

  AUTHORS: Weilin Nie, Cheng Wang

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

  JOURNAL NAME: Journal of Applied Mathematics and Physics, Vol.5 No.4, April 30, 2017

  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.