No Free Lunch in "Privacy for Free: How does Dataset Condensation Help Privacy"

29 September 2022

Papers citing "No Free Lunch in "Privacy for Free: How does Dataset Condensation Help Privacy""

6 / 6 papers shown

Title
Membership Inference Attacks Cannot Prove that a Model Was Trained On Your Data Jie Zhang Debeshee Das Gautam Kamath Florian Tramèr MIALM MIACV 235 16 1 29 Sep 2024
The ICML 2023 Ranking Experiment: Examining Author Self-Assessment in ML/AI Peer Review Buxin Su Jiayao Zhang Natalie Collina Yuling Yan Didong Li Kyunghyun Cho Jianqing Fan Aaron Roth Weijie J. Su 19 4 0 24 Aug 2024
Overcoming Data and Model Heterogeneities in Decentralized Federated Learning via Synthetic Anchors Chun-Yin Huang Kartik Srinivas Xin Zhang Xiaoxiao Li DD 58 6 0 19 May 2024
Dataset Distillation with Convexified Implicit Gradients Noel Loo Ramin Hasani Mathias Lechner Daniela Rus DD 31 41 0 13 Feb 2023
A Comprehensive Survey of Dataset Distillation Shiye Lei Dacheng Tao DD 31 87 0 13 Jan 2023
Systematic Evaluation of Privacy Risks of Machine Learning Models Liwei Song Prateek Mittal MIACV 196 358 0 24 Mar 2020