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Jeremy Seeman
Jeremy Seeman
Data Science Fellow, University of Michigan
Verified email at umich.edu
Title
Cited by
Cited by
Year
Perceived risk, political polarization, and the willingness to follow COVID-19 mitigation guidelines
R Block Jr, M Burnham, K Kahn, R Peng, J Seeman, C Seto
Social Science & Medicine 305, 115091, 2022
212022
Statistical data privacy: a song of privacy and utility
A Slavković, J Seeman
Annual Review of Statistics and Its Application 10, 189-218, 2023
152023
Private posterior inference consistent with public information: A case study in small area estimation from synthetic census data
J Seeman, A Slavkovic, M Reimherr
Privacy in Statistical Databases: UNESCO Chair in Data Privacy …, 2020
132020
Exact privacy guarantees for markov chain implementations of the exponential mechanism with artificial atoms
J Seeman, M Reimherr, A Slavković
Advances in Neural Information Processing Systems 34, 13125-13136, 2021
102021
Between Privacy and Utility: On Differential Privacy in Theory and Practice
J Seeman, D Susser
Available at SSRN 4283836, 2022
62022
Formal Privacy for Partially Private Data
J Seeman, M Reimherr, A Slavkovic
arXiv preprint arXiv:2204.01102, 2022
62022
A formal privacy framework for partially private data
J Seeman, A Slavkovic, M Reimherr
arXiv e-prints, arXiv: 2204.01102, 2022
6*2022
Framing Effects in the Operationalization of Differential Privacy Systems as Code-Driven Law
J Seeman
International Conference on Computer Ethics 1 (1), 2023
32023
Active Camera Stabilization from High Altitude Balloons
MA Bowman, J Seeman, K Walczak
Academic High Altitude Conference 2017 (1), 2017
22017
Privately Answering Queries on Skewed Data via Per Record Differential Privacy
J Seeman, W Sexton, D Pujol, A Machanavajjhala
arXiv preprint arXiv:2310.12827, 2023
2023
Theoretical and Applied Problems in Partially Private Data
J Seeman
2023
Exact Privacy Guarantees for Markov Chain Implementations of the Exponential Mechanism
J Seeman, M Reimherr, A Slavkovic
2022 Virtual Joint Mathematics Meetings (JMM 2022), 2021
2021
A Roadmap for Greater Public Use of Privacy-Sensitive Government Data: Workshop Report Chris Clifton (Purdue University) Bradley Malin (Vanderbilt University Medical Center)
A Oganian, R Raskar, V Sharma, W Xia, J Seeman, Z Wan, A Singh
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Articles 1–13