Follow
Nikola Konstantinov
Nikola Konstantinov
Tenure-track faculty, INSAIT
Verified email at insait.ai - Homepage
Title
Cited by
Cited by
Year
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
4732018
Robust Learning from Untrusted Sources
N Konstantinov, C Lampert
International Conference on Machine Learning (ICML), 2019
672019
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
422018
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
232020
Fairness-aware PAC learning from corrupted data
N Konstantinov, CH Lampert
Journal of Machine Learning Research 23 (160), 1-60, 2022
222022
Data Leakage in Federated Averaging
DI Dimitrov, M Balunovic, N Konstantinov, M Vechev
Transactions on Machine Learning Research, 2022
102022
FLEA: Provably Fair Multisource Learning from Unreliable Training Data
E Iofinova, N Konstantinov, CH Lampert
arXiv preprint arXiv:2106.11732, 2021
82021
Fairness Through Regularization for Learning to Rank
N Konstantinov, CH Lampert
arXiv preprint arXiv:2102.05996, 2021
72021
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
62022
Robustness and fairness in machine learning
NH Konstantinov
12022
Incentivizing Honesty among Competitors in Collaborative Learning
FE Dorner, N Konstantinov, GS Pashaliev, M Vechev
The Second Workshop on New Frontiers in Adversarial Machine Learning, 2023
2023
Strategic Data Sharing between Competitors
N Tsoy, N Konstantinov
To appear in: Conference on Neural Information Processing Systems (NeurIPS …, 2023
2023
Incentivizing Honesty among Competitors in Collaborative Learning and Optimization
FE Dorner, N Konstantinov, G Pashaliev, M Vechev
To appear in: Conference on Neural Information Processing Systems (NeurIPS …, 2023
2023
Human-Guided Fair Classification for Natural Language Processing
FE Dorner, M Peychev, N Konstantinov, N Goel, E Ash, M Vechev
arXiv preprint arXiv:2212.10154, 2022
2022
The system can't perform the operation now. Try again later.
Articles 1–14