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2020 – today
- 2025
[j14]Jorge C.-Rella
, Gerda Claeskens, Ricardo Cao, Juan Manuel Vilar:
Instance-dependent cost-sensitive parametric learning. Neurocomputing 615: 128875 (2025)- 2023
- [j13]Eugen Pircalabelu, Gerda Claeskens:
Linear Manifold Modeling and Graph Estimation based on Multivariate Functional Data with Different Coarseness Scales. J. Comput. Graph. Stat. 32(2): 378-387 (2023) - 2020
- [j12]Eugen Pircalabelu, Gerda Claeskens:
Community-Based Group Graphical Lasso. J. Mach. Learn. Res. 21: 64:1-64:32 (2020)
2010 – 2019
- 2017
- [j11]Lore Dirick, Gerda Claeskens, Bart Baesens:
Time to default in credit scoring using survival analysis: a benchmark study. J. Oper. Res. Soc. 68(6): 652-665 (2017) - [j10]Eugen Pircalabelu, Gerda Claeskens, Irène Gijbels:
Copula directed acyclic graphs. Stat. Comput. 27(1): 55-78 (2017) - [i1]Jelena Bradic, Gerda Claeskens, Thomas Gueuning:
Fixed effects testing in high-dimensional linear mixed models. CoRR abs/1708.04887 (2017) - 2016
- [j9]Aimée Backiel, Bart Baesens, Gerda Claeskens:
Predicting time-to-churn of prepaid mobile telephone customers using social network analysis. J. Oper. Res. Soc. 67(9) (2016) - [j8]Thomas Gueuning, Gerda Claeskens:
Confidence intervals for high-dimensional partially linear single-index models. J. Multivar. Anal. 149: 13-29 (2016) - [j7]Eugen Pircalabelu, Gerda Claeskens:
Focused model selection for social networks. Soc. Networks 46: 76-86 (2016) - 2015
- [j6]Lore Dirick, Gerda Claeskens, Bart Baesens:
An Akaike information criterion for multiple event mixture cure models. Eur. J. Oper. Res. 241(2): 449-457 (2015) - [j5]Eugen Pircalabelu, Gerda Claeskens, Lourens J. Waldorp:
A focused information criterion for graphical models. Stat. Comput. 25(6): 1071-1092 (2015) - [c3]Aimée Backiel, Yannick Verbinnen, Bart Baesens, Gerda Claeskens:
Combining Local and Social Network Classifiers to Improve Churn Prediction. ASONAM 2015: 651-658 - 2014
- [j4]S. Ejaz Ahmed, Gerda Claeskens, Hidetoshi Shimodaira, Stefan Van Aelst:
Special issue on Model Selection and High Dimensional Data Reduction. Comput. Stat. Data Anal. 71: 652-653 (2014) - [c2]Aimée Backiel, Bart Baesens, Gerda Claeskens:
Mining Telecommunication Networks to Enhance Customer Lifetime Predictions. ICAISC (2) 2014: 15-26 - 2012
- [j3]Leen Slaets, Gerda Claeskens, Mia Hubert:
Phase and amplitude-based clustering for functional data. Comput. Stat. Data Anal. 56(7): 2360-2374 (2012) - 2011
- [r3]Maarten Jansen, Gerda Claeskens:
Cramér-Rao Inequality. International Encyclopedia of Statistical Science 2011: 322-323 - [r2]Walter Zucchini, Gerda Claeskens, Georges Nguefack-Tsague:
Model Selection. International Encyclopedia of Statistical Science 2011: 830-833 - [r1]Maarten Jansen, Gerda Claeskens:
Nonparametric Estimation. International Encyclopedia of Statistical Science 2011: 959-962 - 2010
- [j2]Fabrizio Consentino, Gerda Claeskens:
Order selection tests with multiply imputed data. Comput. Stat. Data Anal. 54(10): 2284-2295 (2010)
2000 – 2009
- 2008
- [j1]Gerda Claeskens, Christophe Croux, Johan Van Kerckhoven:
An Information Criterion for Variable Selection in Support Vector Machines. J. Mach. Learn. Res. 9: 541-558 (2008)
1990 – 1999
- 1998
- [c1]Geert Molenberghs, Helena Geys, Lieven Declerck, Gerda Claeskens, Marc Aerts:
Analysis of Clustered Multivariate Data from Developmental Toxicity Studies. COMPSTAT 1998: 3-14
Coauthor Index
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