Invited Open Problem: Does Differential Privacy Make PAC Learning Much Harder?

@inproceedings{DBLP:conf/colt/NissimST26,
  author = {Nissim, Kobbi and Stemmer, Uri and Tsfadia, Eliad},
  editor = {Hanneke, Steve and Lattimore, Tor},
  title = {Invited Open Problem: Does Differential Privacy Make {PAC} Learning
                    Much Harder?},
  booktitle = {The Thirty Ninth Annual Conference on Learning Theory, June 29 - July
                    3, 2026, San Diego, California, {USA}},
  series = {Proceedings of Machine Learning Research},
  volume = {336},
  pages = {7129--7135},
  publisher = {{PMLR}},
  year = {2026},
  url = {https://proceedings.mlr.press/v336/nissim26a.html},
  timestamp = {Sat, 18 Jul 2026 01:00:00 +0200},
  biburl = {https://dblp.org/rec/conf/colt/NissimST26.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}