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| Title | Privacy - preserving Distributed Calculation Methods of a Least - squares Estimator for Linear Regression Models (in Japanese) |
|---|---|
| Authors | Tota Suko 、Shunsuke Horii 、Manabu Kobayashi 、Masayuki Goto 、Toshiyasu Matsushima 、Shigeichi Hirasawa |
| Released Year | 2014 |
| Format | Journal |
| Category | Knowledge information processing |
| Jounal Name | |
| Jounal Page | vol.65, no.2, pp.78-88 |
| Published Year | 2014 |
| Published Month | 7 |
| Abstract （English） |
In this paper, we study a privacy preserving linear regression analysis. We propose a new protocol of a distributed calculation method that calculates a least squares estimator, in the case that two parties have different types of explanatory variables. We show the security of privacy in the proposed protocol. Because the protocol have iterative calculations, we evaluate the number of iterations via nu- merical experiments. Finally, we show an extended protocol that is a distributed calculation method for k parties. |
| Note （English） |
3 |
| Manuscript | |
| Presentation |
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