A Blessing of Dimensionality in Membership Inference through
Regularization

A Blessing of Dimensionality in Membership Inference through Regularization

27 May 2022

Richard G. Baraniuk

Papers citing "A Blessing of Dimensionality in Membership Inference through Regularization"

17 / 17 papers shown

Title
Trustworthy AI on Safety, Bias, and Privacy: A Survey Xingli Fang Jianwei Li Varun Mulchandani Jung-Eun Kim 42 0 0 11 Feb 2025
The Impact of Generalization Techniques on the Interplay Among Privacy, Utility, and Fairness in Image Classification Ahmad Hassanpour Amir Zarei Khawla Mallat Anderson Santana de Oliveira Bian Yang 77 0 0 16 Dec 2024
Defending Membership Inference Attacks via Privacy-aware Sparsity Tuning Qiang Hu Hengxiang Zhang Hongxin Wei 26 1 0 09 Oct 2024
GLiRA: Black-Box Membership Inference Attack via Knowledge Distillation Andrey V. Galichin Mikhail Aleksandrovich Pautov Alexey Zhavoronkin Oleg Y. Rogov Ivan V. Oseledets AAML 21 1 0 13 May 2024
Center-Based Relaxed Learning Against Membership Inference Attacks Xingli Fang Jung-Eun Kim 41 2 0 26 Apr 2024
Deep Networks Always Grok and Here is Why Ahmed Imtiaz Humayun Randall Balestriero Richard Baraniuk AAML OOD AI4CE 47 19 0 23 Feb 2024
Initialization Matters: Privacy-Utility Analysis of Overparameterized Neural Networks Jiayuan Ye Zhenyu Zhu Fanghui Liu Reza Shokri V. Cevher 30 12 0 31 Oct 2023
Training Dynamics of Deep Network Linear Regions Ahmed Imtiaz Humayun Randall Balestriero Richard Baraniuk 26 3 0 19 Oct 2023
Membership Inference Attacks on DNNs using Adversarial Perturbations Hassan Ali Adnan Qayyum Ala I. Al-Fuqaha Junaid Qadir AAML 24 3 0 11 Jul 2023
Precise Asymptotic Generalization for Multiclass Classification with Overparameterized Linear Models David X. Wu A. Sahai 26 2 0 23 Jun 2023
Gaussian Membership Inference Privacy Tobias Leemann Martin Pawelczyk Gjergji Kasneci 22 15 0 12 Jun 2023
Sparsity in neural networks can improve their privacy Antoine Gonon Léon Zheng Clément Lalanne Quoc-Tung Le Guillaume Lauga Can Pouliquen 39 2 0 20 Apr 2023
Can sparsity improve the privacy of neural networks? Antoine Gonon Léon Zheng Clément Lalanne Quoc-Tung Le Guillaume Lauga Can Pouliquen 18 0 0 11 Apr 2023
Parameters or Privacy: A Provable Tradeoff Between Overparameterization and Membership Inference Jasper Tan Blake Mason Hamid Javadi Richard G. Baraniuk FedML 32 19 0 02 Feb 2022
Differentially Private Fine-tuning of Language Models Da Yu Saurabh Naik A. Backurs Sivakanth Gopi Huseyin A. Inan ... Y. Lee Andre Manoel Lukas Wutschitz Sergey Yekhanin Huishuai Zhang 134 346 0 13 Oct 2021
Extracting Training Data from Large Language Models Nicholas Carlini Florian Tramèr Eric Wallace Matthew Jagielski Ariel Herbert-Voss ... Tom B. Brown D. Song Ulfar Erlingsson Alina Oprea Colin Raffel MLAU SILM 290 1,812 0 14 Dec 2020
Scaling Laws for Neural Language Models Jared Kaplan Sam McCandlish T. Henighan Tom B. Brown B. Chess R. Child Scott Gray Alec Radford Jeff Wu Dario Amodei 228 4,460 0 23 Jan 2020