Nikola H Konstantinov
Graduate School
Lampert Group
9 Publications
2022 | Journal Article | IST-REx-ID: 12495 | 
Iofinova, Eugenia B., et al. “FLEA: Provably Robust Fair Multisource Learning from Unreliable Training Data.” Transactions on Machine Learning Research, ML Research Press, 2022.
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2022 | Journal Article | IST-REx-ID: 10802 |
Konstantinov, Nikola H., and Christoph Lampert. “Fairness-Aware PAC Learning from Corrupted Data.” Journal of Machine Learning Research, vol. 23, ML Research Press, 2022, pp. 1–60.
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| arXiv
2022 | Conference Paper | IST-REx-ID: 13241 |
Konstantinov, Nikola H., and Christoph Lampert. “On the Impossibility of Fairness-Aware Learning from Corrupted Data.” Proceedings of Machine Learning Research, vol. 171, ML Research Press, 2022, pp. 59–83.
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| arXiv
2022 | Thesis | IST-REx-ID: 10799 |
Konstantinov, Nikola H. Robustness and Fairness in Machine Learning. Institute of Science and Technology Austria, 2022, doi:10.15479/at:ista:10799.
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2021 | Preprint | IST-REx-ID: 10803 |
Konstantinov, Nikola H., and Christoph Lampert. “Fairness through Regularization for Learning to Rank.” ArXiv, 2102.05996, doi:10.48550/arXiv.2102.05996.
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2020 | Conference Paper | IST-REx-ID: 8724 |
Konstantinov, Nikola H., et al. “On the Sample Complexity of Adversarial Multi-Source PAC Learning.” Proceedings of the 37th International Conference on Machine Learning, vol. 119, ML Research Press, 2020, pp. 5416–25.
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| arXiv
2019 | Conference Paper | IST-REx-ID: 6590 |
Konstantinov, Nikola H., and Christoph Lampert. “Robust Learning from Untrusted Sources.” Proceedings of the 36th International Conference on Machine Learning, vol. 97, ML Research Press, 2019, pp. 3488–98.
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| arXiv
2018 | Conference Paper | IST-REx-ID: 5962 |
Alistarh, Dan-Adrian, et al. “The Convergence of Stochastic Gradient Descent in Asynchronous Shared Memory.” Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing - PODC ’18, ACM Press, 2018, pp. 169–78, doi:10.1145/3212734.3212763.
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| WoS
| arXiv
2018 | Conference Paper | IST-REx-ID: 6589 |
Alistarh, Dan-Adrian, et al. “The Convergence of Sparsified Gradient Methods.” Advances in Neural Information Processing Systems 31, vol. Volume 2018, Neural Information Processing Systems Foundation, 2018, pp. 5973–83.
[Preprint]
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| Download Preprint (ext.)
| WoS
| arXiv
9 Publications
2022 | Journal Article | IST-REx-ID: 12495 |
Iofinova, Eugenia B., et al. “FLEA: Provably Robust Fair Multisource Learning from Unreliable Training Data.” Transactions on Machine Learning Research, ML Research Press, 2022.
[Published Version]
View
| Files available
| Download Published Version (ext.)
| arXiv
2022 | Journal Article | IST-REx-ID: 10802 |
Konstantinov, Nikola H., and Christoph Lampert. “Fairness-Aware PAC Learning from Corrupted Data.” Journal of Machine Learning Research, vol. 23, ML Research Press, 2022, pp. 1–60.
[Published Version]
View
| Files available
| arXiv
2022 | Conference Paper | IST-REx-ID: 13241 |
Konstantinov, Nikola H., and Christoph Lampert. “On the Impossibility of Fairness-Aware Learning from Corrupted Data.” Proceedings of Machine Learning Research, vol. 171, ML Research Press, 2022, pp. 59–83.
[Preprint]
View
| Files available
| Download Preprint (ext.)
| arXiv
2022 | Thesis | IST-REx-ID: 10799 |
Konstantinov, Nikola H. Robustness and Fairness in Machine Learning. Institute of Science and Technology Austria, 2022, doi:10.15479/at:ista:10799.
[Published Version]
View
| Files available
| DOI
2021 | Preprint | IST-REx-ID: 10803 |
Konstantinov, Nikola H., and Christoph Lampert. “Fairness through Regularization for Learning to Rank.” ArXiv, 2102.05996, doi:10.48550/arXiv.2102.05996.
[Preprint]
View
| Files available
| DOI
| Download Preprint (ext.)
| arXiv
2020 | Conference Paper | IST-REx-ID: 8724 |
Konstantinov, Nikola H., et al. “On the Sample Complexity of Adversarial Multi-Source PAC Learning.” Proceedings of the 37th International Conference on Machine Learning, vol. 119, ML Research Press, 2020, pp. 5416–25.
[Published Version]
View
| Files available
| arXiv
2019 | Conference Paper | IST-REx-ID: 6590 |
Konstantinov, Nikola H., and Christoph Lampert. “Robust Learning from Untrusted Sources.” Proceedings of the 36th International Conference on Machine Learning, vol. 97, ML Research Press, 2019, pp. 3488–98.
[Preprint]
View
| Files available
| Download Preprint (ext.)
| arXiv
2018 | Conference Paper | IST-REx-ID: 5962 |
Alistarh, Dan-Adrian, et al. “The Convergence of Stochastic Gradient Descent in Asynchronous Shared Memory.” Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing - PODC ’18, ACM Press, 2018, pp. 169–78, doi:10.1145/3212734.3212763.
[Preprint]
View
| DOI
| Download Preprint (ext.)
| WoS
| arXiv
2018 | Conference Paper | IST-REx-ID: 6589 |
Alistarh, Dan-Adrian, et al. “The Convergence of Sparsified Gradient Methods.” Advances in Neural Information Processing Systems 31, vol. Volume 2018, Neural Information Processing Systems Foundation, 2018, pp. 5973–83.
[Preprint]
View
| Download Preprint (ext.)
| WoS
| arXiv