COLT 2020 was held online in July, and featured nine papers on differential privacy, as well as a keynote talk by Salil Vadhan. While differential privacy has always had a home in the COLT community, it seems like this year was truly exceptional in terms of the number of results. We link all the content below, including pointers to the papers, videos on Youtube, and the page on the conference website. Please let us know if we missed any papers on differential privacy, either in the comments below or by email.

Keynote

• The Theory and Practice of Differential Privacy (video)
  Salil Vadhan

Papers

• Domain Compression and its Application to Randomness-Optimal Distributed Goodness-of-Fit (video, page)
  Jayadev Acharya, Clément L. Canonne, Yanjun Han, Ziteng Sun, Himanshu Tyagi

• Closure Properties for Private Classification and Online Prediction (video, page)
  Noga Alon, Amos Beimel, Shay Moran, Uri Stemmer

• Pan-Private Uniformity Testing (video, page)
  Kareem Amin, Matthew Joseph, Jieming Mao

• Efficient, Noise-Tolerant, and Private Learning via Boosting (video, page)
  Mark Bun, Marco L. Carmosino, Jessica Sorrell

• PAC Learning with Stable and Private Predictions (video, page)
  Yuval Dagan, Vitaly Feldman

• Locally Private Hypothesis Selection (video, page)
  Sivakanth Gopi, Gautam Kamath, Janardhan D. Kulkarni, Aleksandar Nikolov, Zhiwei Steven Wu, Huanyu Zhang

• Private Mean Estimation of Heavy-Tailed Distributions (video, page)
  Gautam Kamath, Vikrant Singhal, Jonathan Ullman

• Privately Learning Thresholds: Closing the Exponential Gap (video, page)
  Haim Kaplan, Katrina Ligett, Yishay Mansour, Moni Naor, Uri Stemmer

• Reasoning About Generalization via Conditional Mutual Information (video, page)
  Thomas Steinke, Lydia Zakynthinou