11 citations · 16 across the 8 of their papers we have counts for
Showing 2023Show all
2 papers · 1 filter
cs.LG2023
Harnessing large-language models to generate private synthetic text
Alexey Kurakin, Natalia Ponomareva, Umar Syed +2
Differentially private training algorithms like DP-SGD protect sensitive training data by ensuring that trained models do not reveal private information. An alternative approach, w…
cs.LG2023
Private and Communication-Efficient Algorithms for Entropy Estimation
Gecia Bravo-Hermsdorff, Róbert Busa-Fekete, Mohammad Ghavamzadeh +2
Modern statistical estimation is often performed in a distributed setting where each sample belongs to a single user who shares their data with a central server. Users are typicall…