Adam Smith

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Leonid ReyzinAssociate Professor of Computer Science, Boston UniversityVerified email at cs.bu.edu
Yevgeniy DodisProfessor, New York UniversityVerified email at cs.nyu.edu
Cynthia DworkMicrosoft ResearchVerified email at microsoft.com
Kobbi NissimDept. of Computer Science (Georgetown) & Center for Research on Computation and Society (Harvard)Verified email at georgetown.edu
Sofya RaskhodnikovaBoston UniversityVerified email at bu.edu
Rafail OstrovskyDistinguished Professor of Computer Science and Mathematics, UCLAVerified email at cs.ucla.edu
Frank McSherryMaterialize, Inc.Verified email at materialize.io
Jonathan KatzProfessor of Computer Science, University of MarylandVerified email at cs.umd.edu
Shiva KasiviswanathanAmazon Machine LearningVerified email at amazon.com
Jonathan UllmanAssociate Professor of Computer Science, Northeastern UniversityVerified email at ccs.neu.edu
Abhradeep Guha ThakurtaGoogle Research - Brain TeamVerified email at google.com
Raef BassilyAssistant Professor, Computer Science & Engineering, The Ohio State UniversityVerified email at osu.edu
Daniel GottesmanPerimeter Institute for Theoretical PhysicsVerified email at perimeterinstitute.ca
Claude CrépeauMcGill UniversityVerified email at cs.mcgill.ca
Thomas SteinkeGoogle Research, Brain TeamVerified email at google.com
Homin K. LeeDatadogVerified email at columbia.edu
Benjamin FullerUniversity of ConnecticutVerified email at uconn.edu
Ran CanettiProfessor of Computer Science, Boston UniversityVerified email at bu.edu
Dana RonTel Aviv UniversityVerified email at tau.ac.il
Shuchi ChawlaUniversity of Wisconsin - MadisonVerified email at cs.wisc.edu

Adam Smith

Professor of Computer Science, Boston University

Verified email at bu.edu - Homepage

Data privacy cryptography machine learning algorithms information theory


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Calibrating noise to sensitivity in private data analysis C Dwork, F McSherry, K Nissim, A Smith Theory of cryptography conference, 265-284, 2006	5149	2006
Fuzzy extractors: How to generate strong keys from biometrics and other noisy data Y Dodis, L Reyzin, A Smith International conference on the theory and applications of cryptographic …, 2004	3438*	2004
Smooth sensitivity and sampling in private data analysis K Nissim, S Raskhodnikova, A Smith Proceedings of the thirty-ninth annual ACM symposium on Theory of computing …, 2007	926	2007
What can we learn privately? SP Kasiviswanathan, HK Lee, K Nissim, S Raskhodnikova, A Smith Foundations of Computer Science, 2008. FOCS'08. IEEE 49th Annual IEEE …, 2008	767	2008
Private empirical risk minimization: Efficient algorithms and tight error bounds R Bassily, A Smith, A Thakurta 2014 IEEE 55th Annual Symposium on Foundations of Computer Science, 464-473, 2014	475	2014
Composition attacks and auxiliary information in data privacy SR Ganta, SP Kasiviswanathan, A Smith Proceeding of the 14th ACM SIGKDD international conference on Knowledge …, 2008	412	2008
Toward privacy in public databases S Chawla, C Dwork, F McSherry, A Smith, H Wee Theory of Cryptography Conference, 363-385, 2005	349	2005
Authentication of quantum messages H Barnum, C Crépeau, D Gottesman, A Smith, A Tapp The 43rd Annual IEEE Symposium on Foundations of Computer Science, 2002 …, 2002	302	2002
Secure remote authentication using biometric data X Boyen, Y Dodis, J Katz, R Ostrovsky, A Smith annual international conference on the theory and applications of …, 2005	295	2005
Local, private, efficient protocols for succinct histograms R Bassily, A Smith Proceedings of the forty-seventh annual ACM symposium on Theory of computing …, 2015	283	2015
Private convex empirical risk minimization and high-dimensional regression D Kifer, A Smith, A Thakurta Conference on Learning Theory, 25.1-25.40, 2012	274	2012
Robust fuzzy extractors and authenticated key agreement from close secrets Y Dodis, J Katz, L Reyzin, A Smith Advances in Cryptology-CRYPTO 2006, 232-250, 2006	271*	2006
Discovering frequent patterns in sensitive data R Bhaskar, S Laxman, A Smith, A Thakurta Proceedings of the 16th ACM SIGKDD international conference on Knowledge …, 2010	269	2010
Differential privacy for statistics: What we know and what we want to learn C Dwork, A Smith Journal of Privacy and Confidentiality 1 (2), 2010	263	2010
Analyzing graphs with node differential privacy SP Kasiviswanathan, K Nissim, S Raskhodnikova, A Smith Theory of Cryptography Conference, 457-476, 2013	244	2013
Leftover hashing against quantum side information M Tomamichel, C Schaffner, A Smith, R Renner IEEE Transactions on Information Theory 57 (8), 5524-5535, 2011	233	2011
Privacy-preserving statistical estimation with optimal convergence rates A Smith Proceedings of the forty-third annual ACM symposium on Theory of computing …, 2011	216	2011
Private analysis of graph structure V Karwa, S Raskhodnikova, A Smith, G Yaroslavtsev Proceedings of the VLDB Endowment 4 (11), 1146-1157, 2011	215	2011
Algorithmic stability for adaptive data analysis R Bassily, K Nissim, A Smith, T Steinke, U Stemmer, J Ullman SIAM Journal on Computing, STOC16-377-STOC16-405, 2021	203	2021
Correcting errors without leaking partial information Y Dodis, A Smith Proceedings of the thirty-seventh annual ACM symposium on Theory of …, 2005	203	2005

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