Spotlight talks
2019 Spotlight talks
in
Workshop: Privacy in Machine Learning (PriML)
in
Workshop: Privacy in Machine Learning (PriML)
Abstract
1. [Jonathan Lebensold, William Hamilton, Borja Balle and Doina Precup] Actor Critic with Differentially Private Critic (#08)
2. [Andres Munoz, Umar Syed, Sergei Vassilvitskii and Ellen Vitercik] Private linear programming without constraint violations (#17)
3. [Ios Kotsogiannis, Yuchao Tao, Xi He, Ashwin Machanavajjhala, Michael Hay and Gerome Miklau] PrivateSQL: A Differentially Private SQL Query Engine (#27)
4. [Amrita Roy Chowdhury, Chenghong Wang, Xi He, Ashwin Machanavajjhala and Somesh Jha] Crypt$\epsilon$: Crypto-Assisted Differential Privacy on Untrusted Servers (#31)
5. [Jiaming Xu and Dana Yang] Optimal Query Complexity of Private Sequential Learning (#32)
6. [Hsiang Hsu, Shahab Asoodeh and Flavio Calmon] Discovering Information-Leaking Samples and Features (#43)
7. [Martine De Cock, Rafael Dowsley, Anderson Nascimento, Davis Railsback, Jianwei Shen and Ariel Todoki] Fast Secure Logistic Regression for High Dimensional Gene Data (#44)
8. [Giuseppe Vietri, Grace Tian, Mark Bun, Thomas Steinke and Steven Wu] New Oracle-Efficient Algorithms for Private Synthetic Data Release (#45)
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