| Adanet: Adaptive structural learning of artificial neural networks C Cortes, X Gonzalvo, V Kuznetsov, M Mohri, S Yang International conference on machine learning, 874-883, 2017 | 184 | 2017 |
| Learning Theory and Algorithms for Forecasting Non-stationary Time Series. V Kuznetsov, M Mohri NIPS, 541-549, 2015 | 59 | 2015 |
| Multi-class deep boosting V Kuznetsov, M Mohri, U Syed | 58 | 2014 |
| Generalization bounds for time series prediction with non-stationary processes V Kuznetsov, M Mohri International conference on algorithmic learning theory, 260-274, 2014 | 43 | 2014 |
| Structured prediction theory based on factor graph complexity C Cortes, V Kuznetsov, M Mohri, S Yang Advances in Neural Information Processing Systems 29, 2514-2522, 2016 | 39 | 2016 |
| Generalization bounds for non-stationary mixing processes V Kuznetsov, M Mohri Machine Learning 106 (1), 93-117, 2017 | 38 | 2017 |
| Ensemble methods for structured prediction C Cortes, V Kuznetsov, M Mohri International Conference on Machine Learning, 1134-1142, 2014 | 33 | 2014 |
| Time series prediction and online learning V Kuznetsov, M Mohri Conference on Learning Theory, 1190-1213, 2016 | 32 | 2016 |
| Rademacher complexity margin bounds for learning with a large number of classes V Kuznetsov, M Mohri, U Syed ICML Workshop on Extreme Classification: Learning with a Very Large Number …, 2015 | 17 | 2015 |
| Learning n-gram language models from uncertain data V Kuznetsov, H Liao, M Mohri, M Riley, B Roark | 16 | 2016 |
| Foundations of sequence-to-sequence modeling for time series V Kuznetsov, Z Mariet arXiv preprint arXiv:1805.03714, 2018 | 14 | 2018 |
| Adanet: A scalable and flexible framework for automatically learning ensembles C Weill, J Gonzalvo, V Kuznetsov, S Yang, S Yak, H Mazzawi, E Hotaj, ... arXiv preprint arXiv:1905.00080, 2019 | 10 | 2019 |
| Foundations of sequence-to-sequence modeling for time series Z Mariet, V Kuznetsov The 22nd International Conference on Artificial Intelligence and Statistics …, 2019 | 10 | 2019 |
| Discrepancy-based algorithms for non-stationary rested bandits C Cortes, G DeSalvo, V Kuznetsov, M Mohri, S Yang arXiv preprint arXiv:1710.10657, 2017 | 10 | 2017 |
| Kernel extraction via voted risk minimization C Cortes, P Goyal, V Kuznetsov, M Mohri Feature Extraction: Modern Questions and Challenges, 72-89, 2015 | 7 | 2015 |
| On-line learning algorithms for path experts with non-additive losses C Cortes, V Kuznetsov, M Mohri, M Warmuth Conference on Learning Theory, 424-447, 2015 | 7 | 2015 |
| A combinatorial approach for solving certain nested recursions with non-slow solutions A Isgur, V Kuznetsov, SM Tanny Journal of Difference Equations and Applications 19 (4), 605-614, 2013 | 6 | 2013 |
| Discriminative state-space models V Kuznetsov, M Mohri Proceedings of the 31st International Conference on Neural Information …, 2017 | 5 | 2017 |
| Learning ensembles of structured prediction rules C Cortes, V Kuznetsov, M Mohri Proceedings of the 52nd Annual Meeting of the Association for Computational …, 2014 | 5 | 2014 |
| Theory and algorithms for forecasting time series V Kuznetsov, M Mohri arXiv preprint arXiv:1803.05814, 2018 | 4 | 2018 |
