| On learnability wih computable learners S Agarwal, N Ananthakrishnan, S Ben-David, T Lechner, R Urner Algorithmic Learning Theory, 48-60, 2020 | 20 | 2020 |
| Learning losses for strategic classification T Lechner, R Urner Proceedings of the AAAI Conference on Artificial Intelligence 36 (7), 7337-7344, 2022 | 11 | 2022 |
| Impossibility results for fair representations T Lechner, S Ben-David, S Agarwal, N Ananthakrishnan arXiv preprint arXiv:2107.03483, 2021 | 11 | 2021 |
| Open Problem: Are all VC-classes CPAC learnable? S Agarwal, N Ananthakrishnan, S Ben-David, T Lechner, R Urner Conference on Learning Theory, 4636-4641, 2021 | 6 | 2021 |
| Strategic classification with unknown user manipulations T Lechner, R Urner, S Ben-David International Conference on Machine Learning, 18714-18732, 2023 | 5 | 2023 |
| Impossibility of Characterizing Distribution Learning--a simple solution to a long-standing problem T Lechner, S Ben-David arXiv preprint arXiv:2304.08712, 2023 | 3 | 2023 |
| Distribution learnability and robustness S Ben-David, A Bie, G Kamath, T Lechner Advances in Neural Information Processing Systems 36, 2024 | 1 | 2024 |
| Inherent Limitations of Multi-Task Fair Representations T Lechner, S Ben-David Conference on Lifelong Learning Agents, 583-603, 2022 | 1 | 2022 |
| Identifying regions of trusted predictions N Ananthakrishnan, S Ben-David, T Lechner, R Urner Uncertainty in Artificial Intelligence, 2125-2134, 2021 | 1 | 2021 |
| Domain Adaptation Under Causal Assumptions T Lechner Tübingen, Germany: Eberhard Karls Universität Tübingen Tübingen, 2018 | 1 | 2018 |
| Adversarially Robust Learning with Uncertain Perturbation Sets T Lechner, V Pathak, R Urner Advances in Neural Information Processing Systems 36, 2024 | | 2024 |
| Pointwise Confidence scores with provable guarantees N Ananthakrishnan, S Ben-David, T Lechner | | 2021 |
Shai Ben-DavidUniverity of Waterloo, CanadaVerified email at uwaterloo.ca
