| Stochastic dominance-based rough set model for ordinal classification W Kot³owski, K Dembczyñski, S Greco, R S³owiñski Information Sciences 178 (21), 4019-4037, 2008 | 172 | 2008 |
| Optimizing the F-measure in multi-label classification: Plug-in rule approach versus structured loss minimization K Dembczynski, A Jachnik, W Kotlowski, W Waegeman, E Hüllermeier International conference on machine learning, 1130-1138, 2013 | 134 | 2013 |
| Bipartite ranking through minimization of univariate loss W Kotlowski, KJ Dembczynski, E Huellermeier Proceedings of the 28th International Conference on Machine Learning (ICML …, 2011 | 108 | 2011 |
| Predicting ads click-through rate with decision rules K Dembczynski, W Kotlowski, D Weiss Workshop on targeting and ranking in online advertising 2008, 2008 | 93 | 2008 |
| ENDER: a statistical framework for boosting decision rules K Dembczyñski, W Kot³owski, R S³owiñski Data Mining and Knowledge Discovery 21, 52-90, 2010 | 90 | 2010 |
| On nonparametric ordinal classification with monotonicity constraints W Kotlowski, R Slowinski IEEE Transactions on Knowledge and Data Engineering 25 (11), 2576-2589, 2012 | 84 | 2012 |
| Rule learning with monotonicity constraints W Kot³owski, R S³owiñski Proceedings of the 26th Annual International Conference on Machine Learning …, 2009 | 77 | 2009 |
| Online PCA with optimal regret J Nie, W Kot³owski, MK Warmuth The Journal of Machine Learning Research 17 (1), 6022-6070, 2016 | 64 | 2016 |
| Consistent multilabel ranking through univariate losses K Dembczynski, W Kotlowski, E Hüllermeier arXiv preprint arXiv:1206.6401, 2012 | 64 | 2012 |
| Maximum likelihood rule ensembles K Dembczyñski, W Kot³owski, R S³owiñski Proceedings of the 25th international conference on Machine learning, 224-231, 2008 | 63 | 2008 |
| Quantum learning: asymptotically optimal classification of qubit states M Guþã, W Kot³owski New Journal of Physics 12 (12), 123032, 2010 | 62 | 2010 |
| Follow the leader with dropout perturbations T Van Erven, W Kot³owski, MK Warmuth Conference on Learning Theory, 949-974, 2014 | 57 | 2014 |
| Ordinal classification with decision rules K Dembczyñski, W Kot³owski, R S³owiñski Mining Complex Data: ECML/PKDD 2007 Third International Workshop, MCD 2007 …, 2008 | 44 | 2008 |
| The many faces of exponential weights in online learning D Hoeven, T Erven, W Kot³owski Conference On Learning Theory, 2067-2092, 2018 | 42 | 2018 |
| Statistical model for rough set approach to multicriteria classification K Dembczyñski, S Greco, W Kot³owski, R S³owiñski Knowledge Discovery in Databases: PKDD 2007: 11th European Conference on …, 2007 | 41 | 2007 |
| Solving regression by learning an ensemble of decision rules K Dembczyñski, W Kot³owski, R S³owiñski Artificial Intelligence and Soft Computing–ICAISC 2008: 9th International …, 2008 | 36 | 2008 |
| Adaptive scale-invariant online algorithms for learning linear models M Kempka, W Kotlowski, MK Warmuth International conference on machine learning, 3321-3330, 2019 | 35 | 2019 |
| Learning rule ensembles for ordinal classification with monotonicity constraints K Dembczyñski, R S³owiñski Fundamenta Informaticae 94 (2), 163-178, 2009 | 35 | 2009 |
| Consistency analysis for binary classification revisited K Dembczyñski, W Kot³owski, O Koyejo, N Natarajan International Conference on Machine Learning, 961-969, 2017 | 34 | 2017 |
| Surrogate regret bounds for generalized classification performance metrics W Kotlowski, K Dembczyñski Asian Conference on Machine Learning, 301-316, 2016 | 31 | 2016 |
