Bounding Information Leakage in Machine Learning

9 May 2021

Papers citing "Bounding Information Leakage in Machine Learning"

9 / 9 papers shown

Title
Membership Inference Risks in Quantized Models: A Theoretical and Empirical Study Eric Aubinais Philippe Formont Pablo Piantanida Elisabeth Gassiat 43 0 0 10 Feb 2025
Synthetic Data, Similarity-based Privacy Metrics, and Regulatory (Non-)Compliance Georgi Ganev 32 0 0 24 Jul 2024
Fundamental Limits of Membership Inference Attacks on Machine Learning Models Eric Aubinais Elisabeth Gassiat Pablo Piantanida MIACV 48 2 0 20 Oct 2023
Amplifying Membership Exposure via Data Poisoning Yufei Chen Chao Shen Yun Shen Cong Wang Yang Zhang AAML 43 27 0 01 Nov 2022
Parameters or Privacy: A Provable Tradeoff Between Overparameterization and Membership Inference Jasper Tan Blake Mason Hamid Javadi Richard G. Baraniuk FedML 34 19 0 02 Feb 2022
Enhanced Membership Inference Attacks against Machine Learning Models Jiayuan Ye Aadyaa Maddi S. K. Murakonda Vincent Bindschaedler Reza Shokri MIALM MIACV 19 231 0 18 Nov 2021
Systematic Evaluation of Privacy Risks of Machine Learning Models Liwei Song Prateek Mittal MIACV 196 358 0 24 Mar 2020
Machine Unlearning: Linear Filtration for Logit-based Classifiers Thomas Baumhauer Pascal Schöttle Matthias Zeppelzauer MU 104 130 0 07 Feb 2020
DeepSurv: Personalized Treatment Recommender System Using A Cox Proportional Hazards Deep Neural Network Jared Katzman Uri Shaham Jonathan Bates A. Cloninger Tingting Jiang Y. Kluger BDL CML OOD 106 1,231 0 02 Jun 2016