Statistical Privacy Guarantees of Machine Learning Preprocessing Techniques
Authors: Ashly Lau, Jonathan Passerat-Palmbach | Published: 2021-09-06
プライバシー評価
Private Multi-Task Learning: Formulation and Applications to Federated Learning
Authors: Shengyuan Hu, Zhiwei Steven Wu, Virginia Smith | Published: 2021-08-30 | Updated: 2023-10-17
Mitigating Statistical Bias within Differentially Private Synthetic Data
Authors: Sahra Ghalebikesabi, Harrison Wilde, Jack Jewson, Arnaud Doucet, Sebastian Vollmer, Chris Holmes | Published: 2021-08-24 | Updated: 2022-05-19
Privacy-Preserving Machine Learning: Methods, Challenges and Directions
Authors: Runhua Xu, Nathalie Baracaldo, James Joshi | Published: 2021-08-10 | Updated: 2021-09-22
Every Query Counts: Analyzing the Privacy Loss of Exploratory Data Analyses
Authors: Saskia Nuñez von Voigt, Mira Pauli, Johanna Reichert, Florian Tschorsch | Published: 2020-08-27
Deep Active Learning with Crowdsourcing Data for Privacy Policy Classification
Authors: Wenjun Qiu, David Lie | Published: 2020-08-07
More Than Privacy: Applying Differential Privacy in Key Areas of Artificial Intelligence
Authors: Tianqing Zhu, Dayong Ye, Wei Wang, Wanlei Zhou, Philip S. Yu | Published: 2020-08-05
Unacceptable, where is my privacy? Exploring Accidental Triggers of Smart Speakers
Authors: Lea Schönherr, Maximilian Golla, Thorsten Eisenhofer, Jan Wiele, Dorothea Kolossa, Thorsten Holz | Published: 2020-08-02
LDP-FL: Practical Private Aggregation in Federated Learning with Local Differential Privacy
Authors: Lichao Sun, Jianwei Qian, Xun Chen | Published: 2020-07-31 | Updated: 2021-05-21
Efficient Sparse Secure Aggregation for Federated Learning
Authors: Constance Beguier, Mathieu Andreux, Eric W. Tramel | Published: 2020-07-29 | Updated: 2021-10-18