An Overview of Privacy in Machine Learning

18 May 2020

Papers citing "An Overview of Privacy in Machine Learning"

9 / 9 papers shown

Title
On the Privacy-Preserving Properties of Spiking Neural Networks with Unique Surrogate Gradients and Quantization Levels Ayana Moshruba Shay Snyder Hamed Poursiami Maryam Parsa AAML 71 2 0 25 Feb 2025
Are Neuromorphic Architectures Inherently Privacy-preserving? An Exploratory Study Ayana Moshruba Ihsen Alouani Maryam Parsa AAML 46 3 0 24 Feb 2025
Patchwork Learning: A Paradigm Towards Integrative Analysis across Diverse Biomedical Data Sources Suraj Rajendran Weishen Pan M. Sabuncu Yong Chen Jiayu Zhou Fei Wang 49 14 0 10 May 2023
Can Querying for Bias Leak Protected Attributes? Achieving Privacy With Smooth Sensitivity Faisal Hamman Jiahao Chen Sanghamitra Dutta 17 9 0 03 Nov 2022
Survey: Leakage and Privacy at Inference Time Marija Jegorova Chaitanya Kaul Charlie Mayor Alison Q. OÑeil Alexander Weir Roderick Murray-Smith Sotirios A. Tsaftaris PILM MIACV 17 71 0 04 Jul 2021
Membership Inference Attacks on Machine Learning: A Survey Hongsheng Hu Z. Salcic Lichao Sun Gillian Dobbie Philip S. Yu Xuyun Zhang MIACV 30 412 0 14 Mar 2021
R-GAP: Recursive Gradient Attack on Privacy Junyi Zhu Matthew Blaschko FedML 6 132 0 15 Oct 2020
Synthetic Observational Health Data with GANs: from slow adoption to a boom in medical research and ultimately digital twins? Jeremy Georges-Filteau Elisa Cirillo SyDa AI4CE 28 17 0 27 May 2020
Slalom: Fast, Verifiable and Private Execution of Neural Networks in Trusted Hardware Florian Tramèr Dan Boneh FedML 114 395 0 08 Jun 2018