| A bias-variance-privacy trilemma for statistical estimation G Kamath, A Mouzakis, M Regehr, V Singhal, T Steinke, J Ullman arXiv preprint arXiv:2301.13334, 2023 | 12 | 2023 |
| An elementary proof that Q-learning converges almost surely MT Regehr, A Ayoub arXiv preprint arXiv:2108.02827, 2021 | 9 | 2021 |
| 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 | 5 | 2020 |
| Avoiding Pitfalls for Privacy Accounting of Subsampled Mechanisms under Composition CJ Lebeda, M Regehr, G Kamath, T Steinke arXiv preprint arXiv:2405.20769, 2024 | 2 | 2024 |
| 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 |
