Mitigating Privacy Risk in Membership Inference by Convex-Concave Loss

8 February 2024

Papers citing "Mitigating Privacy Risk in Membership Inference by Convex-Concave Loss"

9 / 9 papers shown

Title
Efficient Membership Inference Attacks by Bayesian Neural Network Zhenlong Liu Wenyu Jiang Feng Zhou Hongxin Wei MIALM 66 1 0 10 Mar 2025
Trustworthy AI on Safety, Bias, and Privacy: A Survey Xingli Fang Jianwei Li Varun Mulchandani Jung-Eun Kim 40 0 0 11 Feb 2025
Parameters or Privacy: A Provable Tradeoff Between Overparameterization and Membership Inference Jasper Tan Blake Mason Hamid Javadi Richard G. Baraniuk FedML 26 19 0 02 Feb 2022
Federated Learning with Local Differential Privacy: Trade-offs between Privacy, Utility, and Communication Muah Kim Onur Gunlu Rafael F. Schaefer FedML 101 118 0 09 Feb 2021
Membership Inference Attack on Graph Neural Networks Iyiola E. Olatunji Wolfgang Nejdl Megha Khosla AAML 34 97 0 17 Jan 2021
Systematic Evaluation of Privacy Risks of Machine Learning Models Liwei Song Prateek Mittal MIACV 185 358 0 24 Mar 2020
A Simple Convergence Proof of Adam and Adagrad Alexandre Défossez Léon Bottou Francis R. Bach Nicolas Usunier 56 143 0 05 Mar 2020
Densely Connected Convolutional Networks Gao Huang Zhuang Liu L. V. D. van der Maaten Kilian Q. Weinberger PINN 3DV 247 36,237 0 25 Aug 2016
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 282 39,170 0 01 Sep 2014