Oct 20, 2019 · This paper presents a formal approach to carrying out privacy preserving text perturbation using the notion of dx-privacy designed to achieve ...
Jan 22, 2020 · This paper presents a formal approach to carrying out privacy preserving text perturbation using the notion of d_χ-privacy designed to achieve ...
ABSTRACT. Accurately learning from user data while providing quanti able pri- vacy guarantees provides an opportunity to build better ML models.
PDF | On Jan 20, 2020, Oluwaseyi Feyisetan and others published Privacy- and Utility-Preserving Textual Analysis via Calibrated Multivariate Perturbations |
A solution that helps apply a privacy preserving mechanism to NLP data, using Amazon SageMaker. - sagemaker-privacy-for-nlp/README.
Jan 24, 2020 · Bibliographic details on Privacy- and Utility-Preserving Textual Analysis via Calibrated Multivariate Perturbations.
Privacy and Utility Trade-Off for Textual Analysis via Calibrated ...
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A novel private embedding method called the high dimensional truncated Laplacian mechanism is proposed, which is a non-trivial extension of the truncated ...
We proposed a three-layer privacy protection mechanism for carrying out privacy-preserving text perturbation. This approach allows different levels of privacy ...
Year · Privacy-and utility-preserving textual analysis via calibrated multivariate perturbations. O Feyisetan, B Balle, T Drake, T Diethe. Proceedings of the ...
Apr 4, 2024 · Privacy-and utility- · preserving textual analysis via calibrated mul- · tivariate perturbations. In Proceedings of the. 13th International ...