| The convergence of sparsified gradient methods D Alistarh, T Hoefler, M Johansson, N Konstantinov, S Khirirat, C Renggli Advances in Neural Information Processing Systems, 5973-5983, 2018 | 296 | 2018 |
| Robust Learning from Untrusted Sources N Konstantinov, C Lampert International Conference on Machine Learning (ICML), 2019 | 40 | 2019 |
| The convergence of stochastic gradient descent in asynchronous shared memory D Alistarh, C De Sa, N Konstantinov Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing …, 2018 | 33 | 2018 |
| On the Sample Complexity of Adversarial Multi-Source PAC Learning N Konstantinov, E Frantar, D Alistarh, CH Lampert International Conference on Machine Learning (ICML), 2020 | 12 | 2020 |
| Fairness-Aware PAC Learning from Corrupted Data N Konstantinov, CH Lampert arXiv preprint arXiv:2102.06004, 2021 | 7* | 2021 |
| FLEA: Provably Fair Multisource Learning from Unreliable Training Data E Iofinova, N Konstantinov, CH Lampert arXiv preprint arXiv:2106.11732, 2021 | 2 | 2021 |
| Fairness Through Regularization for Learning to Rank N Konstantinov, CH Lampert arXiv preprint arXiv:2102.05996, 2021 | 1 | 2021 |
| On the Impossibility of Fairness-Aware Learning from Corrupted Data N Konstantinov, CH Lampert Algorithmic Fairness through the Lens of Causality and Robustness workshop …, 2022 | | 2022 |
| Robustness and fairness in machine learning NH Konstantinov | | 2022 |
Dan AlistarhIST AustriaVerified email at ist.ac.at
