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2020 – today
- 2024
[j37]Edoardo Fibbi
, Domenico Perrotta, Francesca Torti, Stefan Van Aelst, Tim Verdonck:
Co-clustering contaminated data: a robust model-based approach. Adv. Data Anal. Classif. 18(1): 121-161 (2024)- [j36]Félix Vandervorst, Wouter Verbeke, Tim Verdonck:
Claims fraud detection with uncertain labels. Adv. Data Anal. Classif. 18(1): 219-243 (2024) - [j35]Dries Cornilly, Lise Tubex, Stefan Van Aelst, Tim Verdonck:
Robust and sparse logistic regression. Adv. Data Anal. Classif. 18(3): 663-679 (2024) - [j34]Robin Van Oirbeek, Jolien Ponnet, Bart Baesens, Tim Verdonck:
Computational Efficient Approximations of the Concordance Probability in a Big Data Setting. Big Data 12(3): 243-268 (2024) - [j33]Toon Vanderschueren, Bart Baesens, Tim Verdonck, Wouter Verbeke:
A new perspective on classification: Optimally allocating limited resources to uncertain tasks. Decis. Support Syst. 179: 114151 (2024) - [j32]Steven Mortier, Amir Hamedpour, Bart Bussmann, Ruth Phoebe Tchana Wandji, Steven Latré, Bjarni D. Sigurdsson, Tom De Schepper, Tim Verdonck:
Inferring the relationship between soil temperature and the normalized difference vegetation index with machine learning. Ecol. Informatics 82: 102730 (2024) - [j31]Tim Verdonck, Bart Baesens, María Óskarsdóttir, Seppe vanden Broucke:
Special issue on feature engineering editorial. Mach. Learn. 113(7): 3917-3928 (2024) - [j30]Jakob Raymaekers, Peter J. Rousseeuw, Tim Verdonck, Ruicong Yao:
Fast linear model trees by PILOT. Mach. Learn. 113(9): 6561-6610 (2024) - [j29]Sarah Leyder, Jakob Raymaekers, Tim Verdonck:
Generalized spherical principal component analysis. Stat. Comput. 34(3): 104 (2024) - [j28]Thomas Decorte, Steven Mortier, Jonas J. Lembrechts, Filip J. R. Meysman, Steven Latré, Erik Mannens, Tim Verdonck:
Missing Value Imputation of Wireless Sensor Data for Environmental Monitoring. Sensors 24(8): 2416 (2024) - [i15]Bruno Deprez, Toon Vanderschueren, Bart Baesens, Tim Verdonck, Wouter Verbeke:
Network Analytics for Anti-Money Laundering - A Systematic Literature Review and Experimental Evaluation. CoRR abs/2405.19383 (2024) - [i14]Christopher Bockel-Rickermann, Toon Vanderschueren, Tim Verdonck, Wouter Verbeke:
Sources of Gain: Decomposing Performance in Conditional Average Dose Response Estimation. CoRR abs/2406.08206 (2024) - [i13]Fernando Coello, Thomas Decorte, Iris Janssens, Steven Mortier, Jordi Sardans, Josep Peñuelas, Tim Verdonck:
Global Crop-Specific Fertilization Dataset from 1961-2019. CoRR abs/2406.10001 (2024) - 2023
- [j27]Simon De Vos, Toon Vanderschueren, Tim Verdonck, Wouter Verbeke:
Robust instance-dependent cost-sensitive classification. Adv. Data Anal. Classif. 17(4): 1057-1079 (2023) - [j26]Arie-Willem de Leeuw, Mathieu Heijboer, Tim Verdonck, Arno J. Knobbe, Steven Latré:
Exploiting sensor data in professional road cycling: personalized data-driven approach for frequent fitness monitoring. Data Min. Knowl. Discov. 37(3): 1125-1153 (2023) - [j25]Thomas Decorte, Jakob Raymaekers, Tim Verdonck:
Interpretable cost-sensitive regression through one-step boosting. Decis. Support Syst. 175: 114024 (2023) - [j24]Christopher Bockel-Rickermann, Tim Verdonck, Wouter Verbeke:
Fraud analytics: A decade of research: Organizing challenges and solutions in the field. Expert Syst. Appl. 232: 120605 (2023) - [j23]Lennert Van der Schraelen, Kristof Stouthuysen, Seppe K. L. M. vanden Broucke, Tim Verdonck:
Regularization oversampling for classification tasks: To exploit what you do not know. Inf. Sci. 635: 169-194 (2023) - [j22]Thomas Servotte, Jakob Raymaekers, Tim Verdonck:
Smart initialisation and approximating loss function for robust regression. Inf. Sci. 651: 119715 (2023) - [j21]Steven Mortier, Renata Turkes, Jorg De Winne, Wannes Van Ransbeeck, Dick Botteldooren, Paul Devos, Steven Latré, Marc Leman, Tim Verdonck:
Classification of Targets and Distractors in an Audiovisual Attention Task Based on Electroencephalography. Sensors 23(23): 9588 (2023) - [j20]Emmanuel Jordy Menvouta, Sven Serneels, Tim Verdonck:
direpack: A Python 3 package for state-of-the-art statistical dimensionality reduction methods. SoftwareX 21: 101282 (2023) - [j19]Jolien Ponnet, Jakob Raymaekers, Tim Verdonck:
Fast thresholded concordance probability for evolutionary optimization. Swarm Evol. Comput. 78: 101260 (2023) - [c6]Ireimis Leguen-devarona, Julio Madera, Héctor R. Gonzalez, Lise Tubex, Tim Verdonck:
Oversampling Method Based Covariance Matrix Estimation in High-Dimensional Imbalanced Classification. IWAIPR 2023: 16-23 - [i12]Yves-Cédric Bauwelinckx, Jan Dhaene, Tim Verdonck, Milan van den Heuvel:
On the causality-preservation capabilities of generative modelling. CoRR abs/2301.01109 (2023) - [i11]Jakob Raymaekers, Peter J. Rousseeuw, Tim Verdonck, Ruicong Yao:
Fast Linear Model Trees by PILOT. CoRR abs/2302.03931 (2023) - [i10]Christopher Bockel-Rickermann, Sam Verboven, Tim Verdonck, Wouter Verbeke:
A Causal Perspective on Loan Pricing: Investigating the Impacts of Selection Bias on Identifying Bid-Response Functions. CoRR abs/2309.03730 (2023) - [i9]Christopher Bockel-Rickermann, Toon Vanderschueren, Jeroen Berrevoets, Tim Verdonck, Wouter Verbeke:
Learning continuous-valued treatment effects through representation balancing. CoRR abs/2309.03731 (2023) - [i8]Nick Berlanger, Noah van Ophoven, Tim Verdonck, Ines Wilms:
Tree-based Forecasting of Day-ahead Solar Power Generation from Granular Meteorological Features. CoRR abs/2312.00090 (2023) - [i7]Steven Mortier, Amir Hamedpour, Bart Bussmann, Ruth Phoebe Tchana Wandji, Steven Latré, Bjarni D. Sigurdsson, Tom De Schepper, Tim Verdonck:
Inferring the relationship between soil temperature and the normalized difference vegetation index with machine learning. CoRR abs/2312.12258 (2023) - 2022
- [j18]Emmanuel Jordy Menvouta, Sven Serneels, Tim Verdonck:
Sparse dimension reduction based on energy and ball statistics. Adv. Data Anal. Classif. 16(4): 951-975 (2022) - [j17]Jakob Raymaekers, Wouter Verbeke, Tim Verdonck:
Weight-of-evidence through shrinkage and spline binning for interpretable nonlinear classification. Appl. Soft Comput. 115: 108160 (2022) - [j16]Félix Vandervorst, Wouter Verbeke, Tim Verdonck:
Data misrepresentation detection for insurance underwriting fraud prevention. Decis. Support Syst. 159: 113798 (2022) - [j15]Sebastiaan Höppner, Bart Baesens, Wouter Verbeke, Tim Verdonck:
Instance-dependent cost-sensitive learning for detecting transfer fraud. Eur. J. Oper. Res. 297(1): 291-300 (2022) - [j14]Toon Vanderschueren, Tim Verdonck, Bart Baesens, Wouter Verbeke:
Predict-then-optimize or predict-and-optimize? An empirical evaluation of cost-sensitive learning strategies. Inf. Sci. 594: 400-415 (2022) - [c5]Toon Vanderschueren, Wouter Verbeke, Bart Baesens, Tim Verdonck:
Instance-dependent cost-sensitive learning: do we really need it? HICSS 2022: 1-9 - [c4]Tim Verdonck, Wouter Verbeke, Maria Óskarsdóttir, Bart Baesens:
Introduction to the Minitrack on Fraud Detection Using Machine Learning. HICSS 2022: 1-2 - [i6]Toon Vanderschueren, Bart Baesens, Tim Verdonck, Wouter Verbeke:
A new perspective on classification: optimally allocating limited resources to uncertain tasks. CoRR abs/2202.04369 (2022) - [i5]Toon Vanderschueren, Robert N. Boute, Tim Verdonck, Bart Baesens, Wouter Verbeke:
Prescriptive maintenance with causal machine learning. CoRR abs/2206.01562 (2022) - [i4]Christopher Bockel-Rickermann, Tim Verdonck, Wouter Verbeke:
Fraud Analytics: A Decade of Research - Organizing Challenges and Solutions in the Field. CoRR abs/2212.04329 (2022) - 2021
- [j13]Bart Baesens, Sebastiaan Höppner, Tim Verdonck:
Data engineering for fraud detection. Decis. Support Syst. 150: 113492 (2021) - [i3]Jakob Raymaekers, Wouter Verbeke, Tim Verdonck:
Weight-of-evidence 2.0 with shrinkage and spline-binning. CoRR abs/2101.01494 (2021) - 2020
- [j12]Peter Filzmoser, Sebastiaan Höppner, Irene Ortner, Sven Serneels, Tim Verdonck:
Cellwise robust M regression. Comput. Stat. Data Anal. 147: 106944 (2020) - [j11]Sebastiaan Höppner, Eugen Stripling, Bart Baesens, Seppe vanden Broucke, Tim Verdonck:
Profit driven decision trees for churn prediction. Eur. J. Oper. Res. 284(3): 920-933 (2020) - [j10]Kris Boudt, Peter J. Rousseeuw, Steven Vanduffel, Tim Verdonck:
The minimum regularized covariance determinant estimator. Stat. Comput. 30(1): 113-128 (2020) - [c3]Leonid Kholkine, Tom De Schepper, Tim Verdonck, Steven Latré:
A Machine Learning Approach for Road Cycling Race Performance Prediction. MLSA@PKDD/ECML 2020: 103-112 - [i2]Bart Baesens, Sebastiaan Höppner, Irene Ortner, Tim Verdonck:
robROSE: A robust approach for dealing with imbalanced data in fraud detection. CoRR abs/2003.11915 (2020)
2010 – 2019
- 2019
- [j9]Michiel Debruyne, Sebastiaan Höppner, Sven Serneels, Tim Verdonck:
Outlyingness: Which variables contribute most? Stat. Comput. 29(4): 707-723 (2019) - 2017
- [j8]Mia Hubert, Tim Verdonck, Özlem Yorulmaz:
Fast robust SUR with economical and actuarial applications. Stat. Anal. Data Min. 10(2): 77-88 (2017) - [i1]Sebastiaan Höppner, Eugen Stripling, Bart Baesens, Seppe vanden Broucke, Tim Verdonck:
Profit Driven Decision Trees for Churn Prediction. CoRR abs/1712.08101 (2017) - 2016
- [j7]Mia Hubert, Tom Reynkens, Eric Schmitt, Tim Verdonck:
Sparse PCA for High-Dimensional Data With Outliers. Technometrics 58(4) (2016) - 2015
- [j6]Mia Hubert, Peter J. Rousseeuw, Dina Vanpaemel, Tim Verdonck:
The DetS and DetMM estimators for multivariate location and scatter. Comput. Stat. Data Anal. 81: 64-75 (2015) - 2014
- [j5]Jozef Van Dyck, Tim Verdonck:
Precision of power-law NHPP estimates for multiple systems with known failure rate scaling. Reliab. Eng. Syst. Saf. 126: 143-152 (2014) - 2011
- [c2]Ahmed Lamkanfi, Serge Demeyer, Quinten David Soetens, Tim Verdonck:
Comparing Mining Algorithms for Predicting the Severity of a Reported Bug. CSMR 2011: 249-258 - 2010
- [j4]Michiel Debruyne, Tim Verdonck:
Robust kernel principal component analysis and classification. Adv. Data Anal. Classif. 4(2-3): 151-167 (2010) - [c1]Tim Verdonck, Mia Hubert, Peter J. Rousseeuw:
DetMCD in a Calibration Framework. COMPSTAT 2010: 589-596
2000 – 2009
- 2009
- [j3]Mia Hubert, Peter J. Rousseeuw, Tim Verdonck:
Robust PCA for skewed data and its outlier map. Comput. Stat. Data Anal. 53(6): 2264-2274 (2009) - [j2]Sven Serneels, Tim Verdonck:
Principal component regression for data containing outliers and missing elements. Comput. Stat. Data Anal. 53(11): 3855-3863 (2009) - 2008
- [j1]Sven Serneels, Tim Verdonck:
Principal component analysis for data containing outliers and missing elements. Comput. Stat. Data Anal. 52(3): 1712-1727 (2008)
Coauthor Index
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last updated on 2024-10-07 22:10 CEST by the dblp team
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