Schedule

  • 08:30 AM Opening by Antti Honkela
  • 08:35 AM Deep Learning with Differential Privacy: Two Approaches by Ilya Mironov
  • 09:20 AM Priv'IT: Private and Sample Efficient Identity Testing by Gautam Kamath
  • 09:40 AM Differentially Private Learning of Undirected Graphical Models using CGMs by Garrett Bernstein
  • 10:00 AM Coffee break & Posters 1
  • 10:30 AM Differentially Private Submodular Maximization: Data Summarization in Disguise by Marko Mitrovic
  • 10:50 AM The Hybrid Model for Privacy and its Benefits by Aleksandra Korolova
  • 11:10 AM Posters 2
  • 12:00 PM Lunch
  • 02:00 PM Privacy-preserving machine learning and data mining using the Sharemind platform by Peeter Laud
  • 02:45 PM Privacy-preserving entity resolution and logistic regression on encrypted data by Giorgio Patrini
  • 03:05 PM Coffee break & Posters 3
  • 03:30 PM Detecting Causative Attacks using Data Provenance by Bryant Chen
  • 03:50 PM Panel discussion Borja Balle, Aleksandra Korolova, Peeter Laud, Jun Sakuma