Jeremy Seeman's Page

See my Google Scholar page for complete updates.

Selected recent works

  • Seeman and Susser. “Between Privacy and Utility: On Differential Privacy in Theory and Practice.” ACM Journal on Responsible Computing, 2023. preprint.
  • Seeman, Sexton, Pujol, and Machanavajjhala. “Privately Answering Queries on Skewed Data via Per Record Differential Privacy.” Theory and Practice of Differential Privacy, 2023, forthcoming at Very Large DataBases, 2024. preprintposter
  • Seeman. “Bettery Privacy Theorists for Better Data Stewards.” Forthcoming at Journal of Privacy and Confidentiality, 2023. preprint
  • Seeman. “Private Treatment Assignment for Causal Experiments.” Theory and Practice of Differential Privacy, 2023. poster
  • Seeman. “Framing Effects in the Operationalization of Differential Privacy Systems as Code-Driven Law.” International Conference on Computer Ethics: Philosophical Enquiry, 2023. article
  • Seeman, Reimherr, and Slavkovic. “Formal Privacy for Partially Private Data.” Under revision at Journal of Machine Learning Research, 2022. preprint
  • Seeman, Reimherr, and Slavkovic. “Exact Privacy Guarantees for Sampling Algorithms Implementing the Exponential Mechanism.” Advances in Neural Information Processing Systems, 2021. article

Selected talks

  • Seeman. “Interfacing Statistics and DP: Method and Mess.” Keynote, International Conference on Theory and Practice of Differential Privacy (TPDP), Boston, MA, 2023. slides
  • Seeman. “Misspecification and Uncertainty Quantification in Differential Privacy.” Invited Talk, Fields Institute Workshop on Differential Privacy and Statistical Data Analysis, Fields Institute, Toronto, ON, 2023. video.