Predict-then-optimize or predict-and-optimize? An empirical evaluation of cost-sensitive learning strategies T Vanderschueren, T Verdonck, B Baesens, W Verbeke Information Sciences 594, 400-415, 2022 | 43 | 2022 |
Optimizing the preventive maintenance frequency with causal machine learning T Vanderschueren, R Boute, T Verdonck, B Baesens, W Verbeke International Journal of Production Economics 258, 108798, 2023 | 12 | 2023 |
Accounting For Informative Sampling When Learning to Forecast Treatment Outcomes Over Time T Vanderschueren, A Curth, W Verbeke, M van der Schaar Proceedings of the 40th International Conference on Machine Learning 202 …, 2023 | 12 | 2023 |
A new perspective on classification: optimally allocating limited resources to uncertain tasks T Vanderschueren, B Baesens, T Verdonck, W Verbeke Decision Support Systems 179, 114151, 2024 | 6 | 2024 |
NOFLITE: Learning to predict individual treatment effect distributions T Vanderschueren, J Berrevoets, W Verbeke Transactions on Machine Learning Research, 2023 | 3 | 2023 |
Metalearners for ranking treatment effects T Vanderschueren, W Verbeke, F Moraes, HM Proença arXiv preprint arXiv:2405.02183, 2024 | 1 | 2024 |
Sources of Gain: Decomposing Performance in Conditional Average Dose Response Estimation C Bockel genannt Rickermann, T Vanderschueren, T Verdonck, ... | | 2024 |
Exploring Learning to Rank for Optimal Treatment Allocation T Vanderschueren, W Verbeke, F Moraes, H Proença 33rd European Conference on Operational Research, Date: 2024/06/30-2024/07 …, 2024 | | 2024 |
A Systematic Review and Experimental Evaluation of Social Network Analytics for Anti-Money Laundering B Deprez, T Vanderschueren, T Verdonck, B Baesens, W Verbeke 33rd European conference on Operational Research, Date: 2024/06/30-2024/07 …, 2024 | | 2024 |
Sources of Gain: Decomposing Performance in Conditional Average Dose Response Estimation C Bockel-Rickermann, T Vanderschueren, T Verdonck, W Verbeke arXiv preprint arXiv:2406.08206, 2024 | | 2024 |
Network Analytics for Anti-Money Laundering--A Systematic Literature Review and Experimental Evaluation B Deprez, T Vanderschueren, W Verbeke, B Baesens, T Verdonck arXiv preprint arXiv:2405.19383, 2024 | | 2024 |
Robust instance-dependent cost-sensitive classification S De Vos, T Vanderschueren, T Verdonck, W Verbeke Advances in Data Analysis and Classification 17 (4), 1057-1079, 2023 | | 2023 |
Learning continuous-valued treatment effects through representation balancing C Bockel-Rickermann, T Vanderschueren, J Berrevoets, T Verdonck, ... arXiv preprint arXiv:2309.03731, 2023 | | 2023 |
CBRNets: Regularizing neural networks to learn continuously-valued treatment effects from observational data C Bockel genannt Rickermann, T Vanderschueren, J Berrevoets, ... Joint conference of Data Science, Statistics & Visualisation and the …, 2023 | | 2023 |
Prescriptive maintenance with causal machine learning R Boute, T Verdonck, B Baesens, W Verbeke, T Vanderschueren Belgian Operational Research Society (ORBEL), 36th Annual Conference …, 2022 | | 2022 |
Robust Instance-dependent Cost-sensitive Learning S De Vos, T Vanderschueren, T Verdonck, W Verbeke 32nd European Conference on Operational Research (EURO), Date: 2022/07/03 …, 2022 | | 2022 |
An empirical evaluation of cost-sensitive learning strategies. T Vanderschueren, B Baesens, W Verbeke, TI Verdonck Eastern European Summer School 2021, Location: Budapest (virtual), 2021 | | 2021 |
Instance-dependent cost-sensitive learning: an empirical evaluation. T Vanderschueren, B Baesens, W Verbeke, T Verdonck ORBEL 2021 Workshop on Business Analytics, Location: Online, 2021 | | 2021 |