Marco Gaboardi
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Differential privacy: An economic method for choosing epsilon
J Hsu, M Gaboardi, A Haeberlen, S Khanna, A Narayan, BC Pierce, ...
2014 IEEE 27th Computer Security Foundations Symposium, 398-410, 2014
Privacy amplification by subsampling: Tight analyses via couplings and divergences
B Balle, G Barthe, M Gaboardi
Advances in neural information processing systems 31, 2018
Differential privacy: A primer for a non-technical audience
A Wood, M Altman, A Bembenek, M Bun, M Gaboardi, J Honaker, ...
Vand. J. Ent. & Tech. L. 21, 209, 2018
Software foundations
BC Pierce, C Casinghino, M Gaboardi, M Greenberg, C Hriţcu, V Sjöberg, ...
Webpage: http://www. cis. upenn. edu/bcpierce/sf/current/index. html, 16, 2010
Linear dependent types for differential privacy
M Gaboardi, A Haeberlen, J Hsu, A Narayan, BC Pierce
Proceedings of the 40th annual ACM SIGPLAN-SIGACT symposium on Principles of …, 2013
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
Linear dependent types and relative completeness
U Dal Lago, M Gaboardi
Logic in Computer Science (LICS), 2011 26th Annual IEEE Symposium on, 133-142, 2011
A core quantitative coeffect calculus
A Brunel, M Gaboardi, D Mazza, S Zdancewic
European Symposium on Programming Languages and Systems, 351-370, 2014
Proving differential privacy via probabilistic couplings
G Barthe, M Gaboardi, B Grégoire, J Hsu, PY Strub
Proceedings of the 31st Annual ACM/IEEE Symposium on Logic in Computer …, 2016
Dual query: Practical private query release for high dimensional data
M Gaboardi, EJG Arias, J Hsu, A Roth, ZS Wu
International Conference on Machine Learning, 1170-1178, 2014
Higher-order approximate relational refinement types for mechanism design and differential privacy
G Barthe, M Gaboardi, EJ Gallego Arias, J Hsu, A Roth, PY Strub
Proceedings of the 42nd Annual ACM SIGPLAN-SIGACT Symposium on Principles of …, 2015
Combining effects and coeffects via grading
M Gaboardi, S Katsumata, D Orchard, F Breuvart, T Uustalu
ACM SIGPLAN Notices 51 (9), 476-489, 2016
Hypothesis testing interpretations and renyi differential privacy
B Balle, G Barthe, M Gaboardi, J Hsu, T Sato
International Conference on Artificial Intelligence and Statistics, 2496-2506, 2020
Bridging the gap between computer science and legal approaches to privacy
K Nissim, A Bembenek, A Wood, M Bun, M Gaboardi, U Gasser, ...
Harv. JL & Tech. 31, 687, 2017
Relational cost analysis
E Çiçek, G Barthe, M Gaboardi, D Garg, J Hoffmann
ACM SIGPLAN Notices 52 (1), 316-329, 2017
Psi ({\Psi}): a private data sharing interface
M Gaboardi, J Honaker, G King, J Murtagh, K Nissim, J Ullman, S Vadhan
arXiv preprint arXiv:1609.04340, 2016
Local private hypothesis testing: Chi-square tests
M Gaboardi, R Rogers
International Conference on Machine Learning, 1626-1635, 2018
Empirical risk minimization in non-interactive local differential privacy revisited
D Wang, M Gaboardi, J Xu
Advances in Neural Information Processing Systems 31, 2018
A relational logic for higher-order programs
A Aguirre, G Barthe, M Gaboardi, D Garg, PY Strub
Proceedings of the ACM on Programming Languages 1 (ICFP), 1-29, 2017
A semantic account of metric preservation
A Azevedo de Amorim, M Gaboardi, J Hsu, S Katsumata, I Cherigui
ACM SIGPLAN Notices 52 (1), 545-556, 2017
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