| Boosting the accuracy of differentially-private histograms through consistency M Hay, V Rastogi, G Miklau, D Suciu arXiv preprint arXiv:0904.0942, 2009 | 757 | 2009 |
| Resisting structural re-identification in anonymized social networks M Hay, G Miklau, D Jensen, D Towsley, P Weis Proceedings of the VLDB Endowment 1 (1), 102-114, 2008 | 742 | 2008 |
| Accurate estimation of the degree distribution of private networks M Hay, C Li, G Miklau, D Jensen 2009 Ninth IEEE International Conference on Data Mining, 169-178, 2009 | 519 | 2009 |
| Anonymizing social networks M Hay, G Miklau, D Jensen, P Weis, S Srivastava Computer science department faculty publication series, 180, 2007 | 501 | 2007 |
| Optimizing linear counting queries under differential privacy C Li, M Hay, V Rastogi, G Miklau, A McGregor Proceedings of the twenty-ninth ACM SIGMOD-SIGACT-SIGART symposium on …, 2010 | 417 | 2010 |
| Learning relational probability trees J Neville, D Jensen, L Friedland, M Hay Proceedings of the ninth ACM SIGKDD international conference on Knowledge …, 2003 | 310 | 2003 |
| A data-and workload-aware algorithm for range queries under differential privacy C Li, M Hay, G Miklau, Y Wang arXiv preprint arXiv:1410.0265, 2014 | 208 | 2014 |
| iReduct: Differential privacy with reduced relative errors X Xiao, G Bender, M Hay, J Gehrke Proceedings of the 2011 ACM SIGMOD International Conference on Management of …, 2011 | 202 | 2011 |
| Principled evaluation of differentially private algorithms using dpbench M Hay, A Machanavajjhala, G Miklau, Y Chen, D Zhang Proceedings of the 2016 International Conference on Management of Data, 139-154, 2016 | 194 | 2016 |
| The matrix mechanism: optimizing linear counting queries under differential privacy C Li, G Miklau, M Hay, A McGregor, V Rastogi The VLDB journal 24, 757-781, 2015 | 194 | 2015 |
| An integrated, conditional model of information extraction and coreference with applications to citation matching B Wellner, A McCallum, F Peng, M Hay arXiv preprint arXiv:1207.4157, 2012 | 192 | 2012 |
| Relationship privacy: output perturbation for queries with joins V Rastogi, M Hay, G Miklau, D Suciu Proceedings of the twenty-eighth ACM SIGMOD-SIGACT-SIGART symposium on …, 2009 | 190 | 2009 |
| Optimizing error of high-dimensional statistical queries under differential privacy R McKenna, G Miklau, M Hay, A Machanavajjhala arXiv preprint arXiv:1808.03537, 2018 | 145 | 2018 |
| Resisting structural re-identification in anonymized social networks M Hay, G Miklau, D Jensen, D Towsley, C Li The VLDB Journal 19, 797-823, 2010 | 138 | 2010 |
| Privatesql: a differentially private sql query engine I Kotsogiannis, Y Tao, X He, M Fanaeepour, A Machanavajjhala, M Hay, ... Proceedings of the VLDB Endowment 12 (11), 1371-1384, 2019 | 132 | 2019 |
| Crowd-blending privacy J Gehrke, M Hay, E Lui, R Pass Annual Cryptology Conference, 479-496, 2012 | 127 | 2012 |
| Pegasus: Data-adaptive differentially private stream processing Y Chen, A Machanavajjhala, M Hay, G Miklau Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications …, 2017 | 118 | 2017 |
| Fair decision making using privacy-protected data D Pujol, R McKenna, S Kuppam, M Hay, A Machanavajjhala, G Miklau Proceedings of the 2020 Conference on Fairness, Accountability, and …, 2020 | 110 | 2020 |
| Benchmarking differentially private synthetic data generation algorithms Y Tao, R McKenna, M Hay, A Machanavajjhala, G Miklau arXiv preprint arXiv:2112.09238, 2021 | 104 | 2021 |
| Principles for accountable algorithms and a social impact statement for algorithms N Diakopoulos, S Friedler, M Arenas, S Barocas, M Hay, B Howe, ... FAT/ML, 2017 | 89 | 2017 |
Gerome MiklauProfessor of Computer Science, University of Massachusetts, AmherstVerified email at cs.umass.edu