On learnability wih computable learners S Agarwal, N Ananthakrishnan, S Ben-David, T Lechner, R Urner Algorithmic Learning Theory, 48-60, 2020 | 22 | 2020 |
Learning losses for strategic classification T Lechner, R Urner Proceedings of the AAAI Conference on Artificial Intelligence 36 (7), 7337-7344, 2022 | 17 | 2022 |
Impossibility results for fair representations T Lechner, S Ben-David, S Agarwal, N Ananthakrishnan arXiv preprint arXiv:2107.03483, 2021 | 14 | 2021 |
Strategic classification with unknown user manipulations T Lechner, R Urner, S Ben-David International Conference on Machine Learning, 18714-18732, 2023 | 6 | 2023 |
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 |
Impossibility of Characterizing Distribution Learning--a simple solution to a long-standing problem T Lechner, S Ben-David arXiv preprint arXiv:2304.08712, 2023 | 5 | 2023 |
Distribution learnability and robustness S Ben-David, A Bie, G Kamath, T Lechner Advances in Neural Information Processing Systems 36, 2024 | 2 | 2024 |
Adversarially robust learning with uncertain perturbation sets T Lechner, V Pathak, R Urner 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 |
Inherent limitations of dimensions for characterizing learnability of distribution classes T Lechner, S Ben-David The Thirty Seventh Annual Conference on Learning Theory, 3353-3374, 2024 | | 2024 |
On the Computability of Robust PAC Learning P Gourdeau, L Tosca, R Urner The Thirty Seventh Annual Conference on Learning Theory, 2092-2121, 2024 | | 2024 |
Score design for multi-criteria incentivization A Kabra, M Karzand, T Lechner, N Srebro, S Wang 5th Symposium on Foundations of Responsible Computing (FORC 2024), 2024 | | 2024 |
Pointwise Confidence scores with provable guarantees N Ananthakrishnan, S Ben-David, T Lechner | | 2021 |