Protection against reconstruction and its applications in private federated learning A Bhowmick, J Duchi, J Freudiger, G Kapoor, R Rogers
arXiv preprint arXiv:1812.00984, 2018
286 2018 Differentially private chi-squared hypothesis testing: Goodness of fit and independence testing M Gaboardi, H Lim, R Rogers, S Vadhan
International conference on machine learning, 2111-2120, 2016
134 2016 Max-information, differential privacy, and post-selection hypothesis testing R Rogers, A Roth, A Smith, O Thakkar
2016 IEEE 57th Annual Symposium on Foundations of Computer Science (FOCS …, 2016
83 2016 Learning with Privacy at Scale DP Team
Apple Machine Learning Journal 1 (8), 2017
79 2017 Lower bounds for locally private estimation via communication complexity J Duchi, R Rogers
Conference on Learning Theory, 1161-1191, 2019
77 2019 Psi M Gaboardi, J Honaker, G King, J Murtagh, K Nissim, J Ullman, S Vadhan, ...
arXiv preprint arXiv:1609.04340, 2016
76 2016 Privacy odometers and filters: Pay-as-you-go composition RM Rogers, A Roth, J Ullman, S Vadhan
Advances in Neural Information Processing Systems, 1921-1929, 2016
72 2016 Local private hypothesis testing: Chi-square tests M Gaboardi, R Rogers
International Conference on Machine Learning, 1626-1635, 2018
56 2018 LinkedIn's Audience Engagements API: A privacy preserving data analytics system at scale R Rogers, S Subramaniam, S Peng, D Durfee, S Lee, SK Kancha, ...
arXiv preprint arXiv:2002.05839, 2020
51 2020 Locally Private Mean Estimation: M Gaboardi, R Rogers, O Sheffet
The 22nd international conference on artificial intelligence and statistics …, 2019
49 2019 Practical differentially private top-k selection with pay-what-you-get composition D Durfee, RM Rogers
Advances in Neural Information Processing Systems 32, 2019
48 2019 Asymptotically truthful equilibrium selection in large congestion games RM Rogers, A Roth
Proceedings of the fifteenth ACM conference on Economics and computation …, 2014
46 2014 Privatized machine learning using generative adversarial networks A Bhowmick, AH Vyrros, RM Rogers
US Patent App. 15/892,246, 2019
44 2019 Optimal differential privacy composition for exponential mechanisms J Dong, D Durfee, R Rogers
International Conference on Machine Learning, 2597-2606, 2020
38 2020 Do prices coordinate markets? J Hsu, J Morgenstern, R Rogers, A Roth, R Vohra
Proceedings of the forty-eighth annual ACM symposium on Theory of Computing …, 2016
37 2016 A new class of private chi-square tests D Kifer, R Rogers
Proceedings of the 20th International Conference on Artificial Intelligence …, 2016
32 2016 A new class of private chi-square hypothesis tests R Rogers, D Kifer
Artificial Intelligence and Statistics, 991-1000, 2017
30 2017 Inducing approximately optimal flow using truthful mediators R Rogers, A Roth, J Ullman, ZS Wu
Proceedings of the sixteenth ACM conference on Economics and computation …, 2015
20 2015 Bounding, concentrating, and truncating: Unifying privacy loss composition for data analytics M Cesar, R Rogers
Algorithmic Learning Theory, 421-457, 2021
18 2021 Protection Against Reconstruction and Its Applications in Private Federated Learning. 2019 A Bhowmick, J Duchi, J Freudiger, G Kapoor, R Rogers
arXiv preprint arXiv:1812.00984, 1812
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Aaron RothProfessor of Computer Science, University of PennsylvaniaGeverifieerd e-mailadres voor cis.upenn.edu
