| 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 | 623 | 2018 |
| Robust Learning from Untrusted Sources N Konstantinov, C Lampert International Conference on Machine Learning (ICML), 2019 | 85 | 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 | 47 | 2018 |
| Data Leakage in Federated Averaging DI Dimitrov, M Balunovic, N Konstantinov, M Vechev Transactions on Machine Learning Research (TMLR), 2022 | 34 | 2022 |
| Fairness-aware PAC learning from corrupted data N Konstantinov, CH Lampert Journal of Machine Learning Research 23 (160), 1-60, 2022 | 32 | 2022 |
| 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 | 24 | 2020 |
| Incentivizing Honesty among Competitors in Collaborative Learning and Optimization FE Dorner, N Konstantinov, G Pashaliev, M Vechev Conference on Neural Information Processing Systems (NeurIPS), 2023, 2023 | 14 | 2023 |
| 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 | 13 | 2022 |
| FLEA: Provably robust fair multisource learning from unreliable training data E Iofinova, N Konstantinov, CH Lampert Transactions on Machine Learning Research (TMLR), 2022 | 11 | 2022 |
| Fairness Through Regularization for Learning to Rank N Konstantinov, CH Lampert arXiv preprint arXiv:2102.05996, 2021 | 10 | 2021 |
| Strategic Data Sharing between Competitors N Tsoy, N Konstantinov Conference on Neural Information Processing Systems (NeurIPS), 2023, 2023 | 9 | 2023 |
| Simplicity Bias of Two-Layer Networks beyond Linearly Separable Data N Tsoy, N Konstantinov arXiv preprint arXiv:2405.17299, 2024 | 8 | 2024 |
| COMPL-AI Framework: A Technical Interpretation and LLM Benchmarking Suite for the EU Artificial Intelligence Act P Guldimann, A Spiridonov, R Staab, N Jovanović, M Vero, V Vechev, ... arXiv preprint arXiv:2410.07959, 2024 | 7 | 2024 |
| Human-Guided Fair Classification for Natural Language Processing FE Dorner, M Peychev, N Konstantinov, N Goel, E Ash, M Vechev International Conference on Learning Representations (ICLR), 2023, 2022 | 7 | 2022 |
| Provable Mutual Benefits from Federated Learning in Privacy-Sensitive Domains N Tsoy, A Mihalkova, T Todorova, N Konstantinov International Conference on Artificial Intelligence and Statistics (AISTATS …, 2024 | 2 | 2024 |
| Robustness and fairness in machine learning NH Konstantinov | 2 | 2022 |
| On the Impact of Performative Risk Minimization for Binary Random Variables N Tsoy, I Kirev, N Rahimiyazdi, N Konstantinov arXiv preprint arXiv:2502.02331, 2025 | | 2025 |
| Incentivizing Truthful Collaboration in Heterogeneous Federated Learning D Chakarov, N Tsoy, K Minchev, N Konstantinov arXiv preprint arXiv:2412.00980, 2024 | | 2024 |
| Measuring the Layer-Wise Impact of Image Shortcuts on Deep Model Features N Tsoy, N Konstantinov Workshop on Spurious Correlation and Shortcut Learning: Foundations and …, 0 | | |
Christoph H. LampertInstitute of Science and Technology Austria (ISTA)Verified email at ist.ac.at
