Automatic Discovery of Privacy-Utility Pareto Fronts

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Automatic Discovery of Privacy-Utility Pareto Fronts

26 May 2019

Javier I. González

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Papers citing "Automatic Discovery of Privacy-Utility Pareto Fronts"

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Title
DPolicy: Managing Privacy Risks Across Multiple Releases with Differential Privacy Nicolas Küchler Alexander Viand Hidde Lycklama Anwar Hithnawi 49 0 0 10 May 2025
Federated Computing -- Survey on Building Blocks, Extensions and Systems René Schwermer R. Mayer Hans-Arno Jacobsen FedML 71 1 0 03 Apr 2024
Regulation Games for Trustworthy Machine Learning Mohammad Yaghini Patty Liu Franziska Boenisch Nicolas Papernot FaML 45 2 0 05 Feb 2024
Automated discovery of trade-off between utility, privacy and fairness in machine learning models Bogdan Ficiu Neil D. Lawrence Andrei Paleyes 76 1 0 27 Nov 2023
Real-world Machine Learning Systems: A survey from a Data-Oriented Architecture Perspective Christian Cabrera Andrei Paleyes Pierre Thodoroff Neil D. Lawrence AI4TS AI4CE OOD 62 7 0 09 Feb 2023
SA-DPSGD: Differentially Private Stochastic Gradient Descent based on Simulated Annealing Jie Fu Zhili Chen Xinpeng Ling 77 1 0 14 Nov 2022
Deep Learning-based Anonymization of Chest Radiographs: A Utility-preserving Measure for Patient Privacy Kai Packhauser Sebastian Gündel Florian Thamm Felix Denzinger Andreas Maier 53 3 0 23 Sep 2022
A penalisation method for batch multi-objective Bayesian optimisation with application in heat exchanger design Andrei Paleyes Henry B. Moss Victor Picheny Piotr Zulawski Felix Newman 77 6 0 27 Jun 2022
On the Importance of Architecture and Feature Selection in Differentially Private Machine Learning Wenxuan Bao L. A. Bauer Vincent Bindschaedler OOD 69 4 0 13 May 2022
The Role of Adaptive Optimizers for Honest Private Hyperparameter Selection Shubhankar Mohapatra Sajin Sasy Xi He Gautam Kamath Om Thakkar 164 33 0 09 Nov 2021
Partial sensitivity analysis in differential privacy Tamara T. Mueller Alexander Ziller Dmitrii Usynin Moritz Knolle F. Jungmann Daniel Rueckert Georgios Kaissis 78 1 0 22 Sep 2021
Efficient Hyperparameter Optimization for Differentially Private Deep Learning Aman Priyanshu Rakshit Naidu Fatemehsadat Mireshghallah Mohammad Malekzadeh 82 5 0 09 Aug 2021
Multi-Objective Learning to Predict Pareto Fronts Using Hypervolume Maximization T. Deist Monika Grewal F. Dankers Tanja Alderliesten Peter A. N. Bosman 72 19 0 08 Feb 2021
Challenges in Deploying Machine Learning: a Survey of Case Studies Andrei Paleyes Raoul-Gabriel Urma Neil D. Lawrence 71 408 0 18 Nov 2020
Tempered Sigmoid Activations for Deep Learning with Differential Privacy Nicolas Papernot Abhradeep Thakurta Shuang Song Steve Chien Ulfar Erlingsson AAML 213 179 0 28 Jul 2020