research
∙
07/01/2023
Gradients Look Alike: Sensitivity is Often Overestimated in DP-SGD
Differentially private stochastic gradient descent (DP-SGD) is the canon...
share
research
∙
04/26/2023
Do SSL Models Have Déjà Vu? A Case of Unintended Memorization in Self-supervised Learning
Self-supervised learning (SSL) algorithms can produce useful image repre...
research
∙
05/10/2022
Sentence-level Privacy for Document Embeddings
User language data can contain highly sensitive personal content. As suc...
research
∙
01/13/2022
Privacy Amplification by Subsampling in Time Domain
Aggregate time-series data like traffic flow and site occupancy repeated...
research
∙
06/11/2021
A Shuffling Framework for Local Differential Privacy
ldp deployments are vulnerable to inference attacks as an adversary can ...
research
∙
04/12/2020
A Non-Parametric Test to Detect Data-Copying in Generative Models
Detecting overfitting in generative models is an important challenge in ...
research
∙
12/09/2019
