Ryan McKenna
Title
Cited by
Cited by
Year
How does code obfuscation impact energy usage?
C Sahin, M Wan, P Tornquist, R McKenna, Z Pearson, WGJ Halfond, ...
Journal of Software: Evolution and Process 28 (7), 565-588, 2016
882016
Optimizing error of high-dimensional statistical queries under differential privacy
R McKenna, G Miklau, M Hay, A Machanavajjhala
arXiv preprint arXiv:1808.03537, 2018
362018
Ektelo: A framework for defining differentially-private computations
D Zhang, R McKenna, I Kotsogiannis, M Hay, A Machanavajjhala, ...
Proceedings of the 2018 International Conference on Management of Data, 115-130, 2018
292018
Machine learning predictions of runtime and IO traffic on high-end clusters
R McKenna, S Herbein, A Moody, T Gamblin, M Taufer
2016 IEEE International Conference on Cluster Computing (CLUSTER), 255-258, 2016
252016
Differentially private learning of undirected graphical models using collective graphical models
G Bernstein, R McKenna, T Sun, D Sheldon, M Hay, G Miklau
arXiv preprint arXiv:1706.04646, 2017
202017
Graphical-model based estimation and inference for differential privacy
R McKenna, D Sheldon, G Miklau
arXiv preprint arXiv:1901.09136, 2019
112019
Fair decision making using privacy-protected data
S Kuppam, R McKenna, D Pujol, M Hay, A Machanavajjhala, G Miklau
arXiv preprint arXiv:1905.12744, 2019
82019
From HPC performance to climate modeling: transforming methods for HPC predictions into models of extreme climate conditions
R McKinney, VK Pallipuram, R Vargas, M Taufer
2015 IEEE 11th International Conference on e-Science, 108-117, 2015
52015
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
42020
A workload-adaptive mechanism for linear queries under local differential privacy
R McKenna, RK Maity, A Mazumdar, G Miklau
arXiv preprint arXiv:2002.01582, 2020
12020
PSynDB: accurate and accessible private data generation
Z Huang, R McKenna, G Bissias, G Miklau, M Hay, A Machanavajjhala
Proceedings of the VLDB Endowment 12 (12), 1918-1921, 2019
12019
εKTELO A Framework for Defining Differentially Private Computations
D Zhang, R McKenna, I Kotsogiannis, G Bissias, M Hay, ...
ACM Transactions on Database Systems (TODS) 45 (1), 1-44, 2020
2020
Permute-and-Flip: A new mechanism for differentially private selection
R McKenna, DR Sheldon
Advances in Neural Information Processing Systems 33, 2020
2020
# 8712; A Framework for Defining Differentially-Private Computations
D Zhang, R McKenna, I Kotsogiannis, G Bissias, M Hay, ...
ACM SIGMOD Record 48 (1), 15-22, 2019
2019
epsilon KTELO: A Framework for Defining Differentially-Private Computations
D Zhang, R McKenna, I Kotsogiannis, G Bissias, M Hay, ...
SIGMOD RECORD 48 (1), 15-22, 2019
2019
Probabilistic Modeling of Situational At Bat Interactions
R McKenna, B Lamet, M Gao, B King
2015
Lessons learned from the NIST DP Synthetic Data Competition
R McKenna, G Miklau
Evaluation 5, 10205, 0
Forecasting Storms in Parallel File Systems
R McKenna, T Gamblin, A Moody, B de Supinski, M Taufer
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Articles 1–18