papers

2022

1. 

   SNAP: Efficient Extraction of Private Properties with Poisoning (IEEE S&P’23 Conditional Accept)

   Harsh Chaudhari, John Abascal, Alina Oprea, Matthew Jagielski, Florian Tramèr, and Jonathan Ullman

   2022

   Bib PDF

     doi = {10.48550/ARXIV.2208.12348},
     author = {Chaudhari, Harsh and Abascal, John and Oprea, Alina and Jagielski, Matthew and Tramèr, Florian and Ullman, Jonathan},
     keywords = {Machine Learning (cs.LG), Cryptography and Security (cs.CR), FOS: Computer and information sciences, FOS: Computer and information sciences},
     title = {SNAP: Efficient Extraction of Private Properties with Poisoning (IEEE S\&P'23 Conditional Accept)},
     publisher = {arXiv},
     year = {2022},
     copyright = {arXiv.org perpetual, non-exclusive license},
     preview = {separation.gif},
   }