A bias-variance-privacy trilemma for statistical estimation G Kamath, A Mouzakis, M Regehr, V Singhal, T Steinke, J Ullman arXiv e-prints, arXiv: 2301.13334, 2023 | 19 | 2023 |
An elementary proof that q-learning converges almost surely MT Regehr, A Ayoub arXiv preprint arXiv:2108.02827, 2021 | 12 | 2021 |
Avoiding pitfalls for privacy accounting of subsampled mechanisms under composition CJ Lebeda, M Regehr, G Kamath, T Steinke arXiv preprint arXiv:2405.20769, 2024 | 7 | 2024 |
Machine learning and graph based approach to automatic right atrial segmentation from magnetic resonance imaging M Regehr, A Volk, M Noga, K Punithakumar 2020 IEEE 17th international symposium on biomedical imaging (ISBI), 826-829, 2020 | 6 | 2020 |
A Bias-Accuracy-Privacy Trilemma for Statistical Estimation G Kamath, A Mouzakis, M Regehr, V Singhal, T Steinke, J Ullman Journal of the American Statistical Association, 1-12, 2025 | | 2025 |
Avoiding Pitfalls for Privacy Accounting of Subsampled Mechanisms under Composition C Janos Lebeda, M Regehr, G Kamath, T Steinke arXiv e-prints, arXiv: 2405.20769, 2024 | | 2024 |
A Bias-Variance-Privacy Trilemma for Statistical Estimation M Regehr University of Waterloo, 2023 | | 2023 |
A Brief Survey of Private and Online Learning MT Regehr | | 2022 |
A Strange Square Complex and c3-Locally Testable Codes MT Regehr | | 2022 |