Jonathan Ullman

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Citations	4047	2992
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Adam SmithProfessor of Computer Science, Boston UniversityVerified email at bu.edu
Aaron RothProfessor of Computer Science, University of PennsylvaniaVerified email at cis.upenn.edu
Thomas SteinkeGoogle Research, Brain TeamVerified email at google.com
Salil VadhanVicky Joseph Professor of Computer Science and Applied Mathematics, Harvard UniversityVerified email at g.harvard.edu
Gautam KamathAssistant Professor, University of WaterlooVerified email at uwaterloo.ca
Albert CheuPostdoctoral Fellow, Georgetown UniversityVerified email at georgetown.edu
Kobbi NissimDept. of Computer Science (Georgetown)Verified email at georgetown.edu
Cynthia DworkMicrosoft ResearchVerified email at microsoft.com
Alina OpreaNortheastern UniversityVerified email at neu.edu
Matthew JagielskiGoogle ResearchVerified email at google.com
Vikrant SinghalPostdoctoral Fellow, University of WaterlooVerified email at northeastern.edu
Zhiwei Steven WuCarnegie Mellon UniversityVerified email at andrew.cmu.edu
Mallesh M. PaiRice UniversityVerified email at rice.edu
Michael KearnsProfessor of Computer Science, University of PennsylvaniaVerified email at cis.upenn.edu
Raef BassilyAssistant Professor, Computer Science & Engineering, The Ohio State UniversityVerified email at osu.edu
Justin ThalerGeorgetown UniversityVerified email at georgetown.edu
Lydia ZakynthinouPhD Student, Northeastern UniversityVerified email at northeastern.edu
Anupam GuptaProfessor of Computer Science at Carnegie Mellon UniversityVerified email at cs.cmu.edu
Moritz HardtDirector, Max Planck Institute for Intelligent SystemsVerified email at is.mpg.de
Uri StemmerTel Aviv UniversityVerified email at tau.ac.il

Jonathan Ullman

Associate Professor of Computer Science, Northeastern University

Verified email at ccs.neu.edu - Homepage

Differential Privacy Machine Learning Theory Cryptography


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Distributed Differential Privacy via Shuffling A Cheu, A Smith, J Ullman, D Zeber, M Zhilyaev	267	2018
Algorithmic stability for adaptive data analysis R Bassily, K Nissim, A Smith, T Steinke, U Stemmer, J Ullman Proceedings of the forty-eighth annual ACM symposium on Theory of Computing …, 2016	261	2016
Iterative constructions and private data release A Gupta, A Roth, J Ullman Theory of Cryptography: 9th Theory of Cryptography Conference, TCC 2012 …, 2012	197	2012
Exposed! a survey of attacks on private data C Dwork, A Smith, T Steinke, J Ullman Annual Review of Statistics and Its Application 4, 61-84, 2017	195	2017
Fingerprinting codes and the price of approximate differential privacy M Bun, J Ullman, S Vadhan SIAM Journal on Computing 47 (5), 1888-1938, 2018	177*	2018
Robust mediators in large games M Kearns, MM Pai, R Rogers, A Roth, J Ullman arXiv preprint arXiv:1512.02698, 2015	159*	2015
Robust traceability from trace amounts C Dwork, A Smith, T Steinke, J Ullman, S Vadhan 2015 IEEE 56th Annual Symposium on Foundations of Computer Science, 650-669, 2015	159	2015
Privately releasing conjunctions and the statistical query barrier A Gupta, M Hardt, A Roth, J Ullman Proceedings of the forty-third annual ACM symposium on Theory of computing …, 2011	154	2011
Between pure and approximate differential privacy T Steinke, J Ullman arXiv preprint arXiv:1501.06095, 2015	128	2015
The price of privately releasing contingency tables and the spectra of random matrices with correlated rows SP Kasiviswanathan, M Rudelson, A Smith, J Ullman Proceedings of the forty-second ACM symposium on Theory of computing, 775-784, 2010	122	2010
Preventing false discovery in interactive data analysis is hard M Hardt, J Ullman Foundations of Computer Science (FOCS), 2014 IEEE 55th Annual Symposium on …, 2014	115	2014
Differentially private fair learning M Jagielski, M Kearns, J Mao, A Oprea, A Roth, S Sharifi-Malvajerdi, ... International Conference on Machine Learning, 3000-3008, 2019	114	2019
PCPs and the hardness of generating private synthetic data J Ullman, S Vadhan Theory of Cryptography: 8th Theory of Cryptography Conference, TCC 2011 …, 2011	106*	2011
Interactive fingerprinting codes and the hardness of preventing false discovery T Steinke, J Ullman Conference on learning theory, 1588-1628, 2015	103	2015
Auditing differentially private machine learning: How private is private sgd? M Jagielski, J Ullman, A Oprea Advances in Neural Information Processing Systems 33, 22205-22216, 2020	102	2020
Answering n^{2+o(1)} counting queries with differential privacy is hard J Ullman SIAM Journal on Computing 45 (2), 473-496, 2016	101	2016
Faster algorithms for privately releasing marginals J Thaler, J Ullman, S Vadhan Automata, Languages, and Programming: 39th International Colloquium, ICALP …, 2012	95	2012
Privately learning high-dimensional distributions G Kamath, J Li, V Singhal, J Ullman Conference on Learning Theory, 1853-1902, 2019	85	2019
Local differential privacy for evolving data M Joseph, A Roth, J Ullman, B Waggoner Advances in Neural Information Processing Systems 31, 2018	73	2018
PSI: a Private data Sharing Interface M Gaboardi, J Honaker, G King, K Nissim, J Ullman, S Vadhan arXiv preprint arXiv:1609.04340, 2016	73	2016

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