Differential Privacy and Machine Learning: a Survey and Review

Differential Privacy and Machine Learning: a Survey and Review

24 December 2014

Zachary Chase Lipton

Papers citing "Differential Privacy and Machine Learning: a Survey and Review"

13 / 13 papers shown

Title
On the Byzantine Fault Tolerance of signSGD with Majority Vote Emanuele Mengoli Luzius Moll Virgilio Strozzi El-Mahdi El-Mhamdi AAML FedML 91 1 0 26 Feb 2025
Bridging Today and the Future of Humanity: AI Safety in 2024 and Beyond Shanshan Han 139 1 0 09 Oct 2024
Personalized Privacy Amplification via Importance Sampling Dominik Fay Sebastian Mair Jens Sjölund 86 0 0 05 Jul 2023
Convergence Rates for Differentially Private Statistical Estimation Kamalika Chaudhuri Daniel J. Hsu FedML 70 50 0 27 Jun 2012
A Learning Theory Approach to Non-Interactive Database Privacy Avrim Blum Katrina Ligett Aaron Roth 84 550 0 10 Sep 2011
Differentially Private Online Learning Prateek Jain Pravesh Kothari Abhradeep Thakurta 42 42 0 01 Sep 2011
Compressive Mechanism: Utilizing Sparse Representation in Differential Privacy Yang D. Li Zhenjie Zhang Marianne Winslett Yifan Yang 59 84 0 18 Jul 2011
Lower bounds in differential privacy Anindya De 81 131 0 12 Jul 2011
Differentially Private Empirical Risk Minimization Kamalika Chaudhuri C. Monteleoni Anand D. Sarwate 121 1,487 0 01 Dec 2009
Learning in a Large Function Space: Privacy-Preserving Mechanisms for SVM Learning Benjamin I. P. Rubinstein Peter L. Bartlett Ling Huang N. Taft 101 295 0 30 Nov 2009
Efficient, Differentially Private Point Estimators Adam D. Smith FedML 71 78 0 27 Sep 2008
What Can We Learn Privately? S. Kasiviswanathan Homin K. Lee Kobbi Nissim Sofya Raskhodnikova Adam D. Smith 123 1,465 0 06 Mar 2008
Composition Attacks and Auxiliary Information in Data Privacy S. R. Ganta S. Kasiviswanathan Adam D. Smith 124 423 0 01 Mar 2008