1 citations · 1 across the 4 of their papers we have counts for
4 papers
On the Impact of Noise in Differentially Private Text Rewriting
Stephen Meisenbacher, Maulik Chevli, Florian Matthes
The field of text privatization often leverages the notion of (DP) to provide formal guarantees in the rewriting or obfuscation of sensitive textual…
A Collocation-based Method for Addressing Challenges in Word-level Metric Differential Privacy
Stephen Meisenbacher, Maulik Chevli, Florian Matthes
Applications of Differential Privacy (DP) in NLP must distinguish between the syntactic level on which a proposed mechanism operates, often taking the form of …
DP-MLM: Differentially Private Text Rewriting Using Masked Language Models
Stephen Meisenbacher, Maulik Chevli, Juraj Vladika +1
The task of text privatization using Differential Privacy has recently taken the form of , in which an input text is obfuscated via the use of generative (…
Privacy-Utility Trade-offs in Neural Networks for Medical Population Graphs: Insights from Differential Privacy and Graph Structure
Tamara T. Mueller, Maulik Chevli, Ameya Daigavane +2
We initiate an empirical investigation into differentially private graph neural networks on population graphs from the medical domain by examining privacy-utility trade-offs at dif…