Dec 1, 2017 · We introduce the notion of Price of Privacy, a novel approach for measuring the impact of privacy protection on the accuracy in the proposed ...
Abstract: Machine learning algorithms have reached mainstream status and are widely deployed in many ap- plications. The accuracy of such algorithms depends ...
Unfortunately, privacy concerns prevent them from straightforwardly doing so. ... In this paper, we model the collaborative training process as a two-player game ...
In this paper, by focusing on a two-player setting, we model the collaborative training process as a two-player game where each player aims to achieve higher ...
The notion of Price of Privacy is introduced, a novel approach for measuring the impact of privacy protection on the accuracy in the proposed framework, ...
Together or Alone: The Price of Privacy in Collaborative Learning. Download PDF · Open Webpage · Balazs Pejo, Qiang Tang, Gergely Biczók. Published: 31 Dec 2018 ...
Alone vs Together. Training together is superior to training alone for both ... Tang: Together or Alone: The Price of. Privacy in Collaborative learning.
In this paper we model the training process as a two player game where each player aims to achieve a higher accuracy while preserving its privacy. We describe 3 ...
For such organizations, a realistic solution is to train machine learning models based on a joint dataset (which is a union of the individual ones).
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Training together is superior to training alone for both datasets and all size ratios. Moreover, the owner of the smaller dataset benefits more from.