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Ryan McKenna · SciRah

Researcher profile · Semantic Scholar

Ryan McKenna

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Ryan McKenna — researcher profile on SciRah

h-index: 14
Works: 20
Citations: 1,261

Most-cited papers

Graphical-model based estimation and inference for differential privacy
Ryan McKenna, D. Sheldon, G. Miklau
2019International Conference on Machine Learning196 citations
Semantic Scholar
Winning the NIST Contest: A scalable and general approach to differentially private synthetic data
Ryan McKenna, G. Miklau, D. Sheldon
2021Journal of Privacy and Confidentiality190 citations Open access
Semantic Scholar
AIM: An Adaptive and Iterative Mechanism for Differentially Private Synthetic Data
Ryan McKenna, Brett Mullins, D. Sheldon, G. Miklau
2022Proceedings of the VLDB Endowment163 citations
Semantic Scholar
Optimizing error of high-dimensional statistical queries under differential privacy
Ryan McKenna, G. Miklau, Michael Hay, Ashwin Machanavajjhala
2018Proceedings of the VLDB Endowment131 citations Open access
Semantic Scholar
Benchmarking Differentially Private Synthetic Data Generation Algorithms
Yu-Chao Tao, Ryan McKenna, Michael Hay, Ashwin Machanavajjhala +1 more
2021arXiv.org127 citations
Semantic Scholar
Fair decision making using privacy-protected data
David Pujol, Ryan McKenna, Satya Kuppam, Michael Hay +2 more
2019FAT*122 citations Open access
Semantic Scholar
Permute-and-Flip: A new mechanism for differentially private selection
Ryan McKenna, D. Sheldon
2020Neural Information Processing Systems68 citations
Semantic Scholar
(Amplified) Banded Matrix Factorization: A unified approach to private training
Christopher A. Choquette-Choo, Arun Ganesh, Ryan McKenna, H. B. McMahan +3 more
2023Neural Information Processing Systems67 citations Open access
Semantic Scholar
EKTELO: A Framework for Defining Differentially-Private Computations
Dan Zhang, Ryan McKenna, Ios Kotsogiannis, G. Bissias +3 more
2018SIGMOD Conference66 citations Open access
Semantic Scholar
HDMM: Optimizing error of high-dimensional statistical queries under differential privacy
Ryan McKenna, G. Miklau, Michael Hay, Ashwin Machanavajjhala
2021Journal of Privacy and Confidentiality28 citations Open access
Semantic Scholar
Differentially Private Learning of Undirected Graphical Models Using Collective Graphical Models
Garrett Bernstein, Ryan McKenna, Tao Sun, D. Sheldon +2 more
2017International Conference on Machine Learning28 citations
Semantic Scholar
Gradient Descent with Linearly Correlated Noise: Theory and Applications to Differential Privacy
Anastasia Koloskova, Ryan McKenna, Zachary B. Charles, J. Rush +1 more
2023Neural Information Processing Systems24 citations Open access
Semantic Scholar
A workload-adaptive mechanism for linear queries under local differential privacy
Ryan McKenna, R. Maity, A. Mazumdar, G. Miklau
2020Proceedings of the VLDB Endowment15 citations Open access
Semantic Scholar
Joint Selection: Adaptively Incorporating Public Information for Private Synthetic Data
Miguel Fuentes, Brett Mullins, Ryan McKenna, G. Miklau +1 more
2024International Conference on Artificial Intelligence and Statistics14 citations
Semantic Scholar
Relaxed Marginal Consistency for Differentially Private Query Answering
Ryan McKenna, Siddhant Pradhan, D. Sheldon, G. Miklau
2021Neural Information Processing Systems13 citations
Semantic Scholar
PSynDB: Accurate and Accessible Private Data Generation
Zhiqi Huang, Ryan McKenna, G. Bissias, G. Miklau +2 more
2019Proceedings of the VLDB Endowment9 citations
Semantic Scholar
Convergence of Gradient Descent with Linearly Correlated Noise and Applications to Differentially Private Learning
Anastasia Koloskova, Ryan McKenna, Zachary B. Charles, Keith Rush +1 more
2023arXiv.org7 citations Open access
Semantic Scholar
#8712;: A Framework for Defining Differentially-Private Computations
Dan Zhang, Ryan McKenna, Ios Kotsogiannis, G. Bissias +3 more
2019SGMD1 citations
Semantic Scholar
Tight End-to-End Accounting for Differentially Private Synthetic Data
Georgi Ganev, Vadym Doroshenko, Arun Ganesh, J. Gómez +2 more
20260 citations
Semantic Scholar
Lessons learned from the NIST DP Synthetic Data Competition
Ryan McKenna, G. Miklau
20190 citations
Semantic Scholar

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