| Itemset mining: A constraint programming perspective T Guns, S Nijssen, L De Raedt Artificial Intelligence 175 (12-13), 1951-1983, 2011 | 255 | 2011 |
| Smart predict-and-optimize for hard combinatorial optimization problems J Mandi, PJ Stuckey, T Guns Proceedings of the AAAI conference on artificial intelligence 34 (02), 1603-1610, 2020 | 240 | 2020 |
| Constraint programming for itemset mining L De Raedt, T Guns, S Nijssen Proceedings of the 14th ACM SIGKDD international conference on Knowledge …, 2008 | 236 | 2008 |
| Decision-focused learning: Foundations, state of the art, benchmark and future opportunities J Mandi, J Kotary, S Berden, M Mulamba, V Bucarey, T Guns, F Fioretto Journal of Artificial Intelligence Research 80, 1623-1701, 2024 | 179 | 2024 |
| Interior point solving for lp-based prediction+ optimisation J Mandi, T Guns Advances in Neural Information Processing Systems 33, 7272-7282, 2020 | 159 | 2020 |
| k-Pattern set mining under constraints T Guns, S Nijssen, L De Raedt IEEE Transactions on Knowledge and Data Engineering 25 (2), 402-418, 2011 | 101 | 2011 |
| Constraint programming for data mining and machine learning L De Raedt, T Guns, S Nijssen Proceedings of the AAAI Conference on Artificial Intelligence 24 (1), 1671-1675, 2010 | 101 | 2010 |
| Decision-focused learning: Through the lens of learning to rank J Mandi, V Bucarey, MMK Tchomba, T Guns International conference on machine learning, 14935-14947, 2022 | 99 | 2022 |
| Correlated itemset mining in ROC space: a constraint programming approach S Nijssen, T Guns, L De Raedt Proceedings of the 15th ACM SIGKDD international conference on Knowledge …, 2009 | 99 | 2009 |
| Contrastive losses and solution caching for predict-and-optimize M Mulamba, J Mandi, M Diligenti, M Lombardi, V Bucarey, T Guns arXiv preprint arXiv:2011.05354, 2020 | 90 | 2020 |
| Constrained clustering using column generation B Babaki, T Guns, S Nijssen International Conference on Integration of Constraint Programming …, 2014 | 84 | 2014 |
| Learning to rank for uplift modeling F Devriendt, J Van Belle, T Guns, W Verbeke IEEE Transactions on Knowledge and Data Engineering 34 (10), 4888-4904, 2020 | 79 | 2020 |
| Increasing modeling language convenience with a universal n-dimensional array, cppy as python-embedded example T Guns Proceedings of the 18th workshop on Constraint Modelling and Reformulation …, 2019 | 73 | 2019 |
| Using shared sell-through data to forecast wholesaler demand in multi-echelon supply chains J Van Belle, T Guns, W Verbeke European Journal of Operational Research 288 (2), 466-479, 2021 | 72 | 2021 |
| Constraint-based sequence mining using constraint programming B Negrevergne, T Guns International Conference on Integration of Constraint Programming …, 2015 | 72 | 2015 |
| An investigation into prediction+ optimisation for the knapsack problem E Demirović, PJ Stuckey, J Bailey, J Chan, C Leckie, K Ramamohanarao, ... International Conference on Integration of Constraint Programming …, 2019 | 67 | 2019 |
| Monitoring urban-freight transport based on GPS trajectories of heavy-goods vehicles S Hadavi, S Verlinde, W Verbeke, C Macharis, T Guns IEEE Transactions on Intelligent Transportation Systems 20 (10), 3747-3758, 2018 | 61 | 2018 |
| Learning constraints in spreadsheets and tabular data S Kolb, S Paramonov, T Guns, L De Raedt Machine Learning 106 (9), 1441-1468, 2017 | 59 | 2017 |
| Coversize: A global constraint for frequency-based itemset mining P Schaus, JOR Aoga, T Guns International Conference on Principles and Practice of Constraint …, 2017 | 59 | 2017 |
| Miningzinc: A declarative framework for constraint-based mining T Guns, A Dries, S Nijssen, G Tack, L De Raedt Artificial Intelligence 244, 6-29, 2017 | 56 | 2017 |
