2 citations · 2 across the 1 of their papers we have counts for
3 papers
Differentially Private Language Models for Secure Data Sharing
Justus Mattern, Zhijing Jin, Benjamin Weggenmann +2
To protect the privacy of individuals whose data is being shared, it is of high importance to develop methods allowing researchers and companies to release textual data while provi…
The Limits of Word Level Differential Privacy
Justus Mattern, Benjamin Weggenmann, Florian Kerschbaum
As the issues of privacy and trust are receiving increasing attention within the research community, various attempts have been made to anonymize textual data. A significant subset…
SynTF: Synthetic and Differentially Private Term Frequency Vectors for Privacy-Preserving Text Mining
Benjamin Weggenmann, Florian Kerschbaum
Text mining and information retrieval techniques have been developed to assist us with analyzing, organizing and retrieving documents with the help of computers. In many cases, it…