108 citations · 165 across the 21 of their papers we have counts for
9 papers · 1 filter
HydaLearn: Highly Dynamic Task Weighting for Multi-task Learning with Auxiliary Tasks
Sam Verboven, Muhammad Hafeez Chaudhary, Jeroen Berrevoets +1
Multi-task learning (MTL) can improve performance on a task by sharing representations with one or more related auxiliary-tasks. Usually, MTL-networks are trained on a composite lo…
Misclassification cost-sensitive ensemble learning: A unifying framework
George Petrides, Wouter Verbeke
Over the years, a plethora of cost-sensitive methods have been proposed for learning on data when different types of misclassification errors incur different costs. Our contributio…
The foundations of cost-sensitive causal classification
Wouter Verbeke, Diego Olaya, Jeroen Berrevoets +2
Classification is a well-studied machine learning task which concerns the assignment of instances to a set of outcomes. Classification models support the optimization of managerial…
Instance-Dependent Cost-Sensitive Learning for Detecting Transfer Fraud
Sebastiaan Höppner, Bart Baesens, Wouter Verbeke +1
Card transaction fraud is a growing problem affecting card holders worldwide. Financial institutions increasingly rely upon data-driven methods for developing fraud detection syste…
A study of the U.S. domestic air transportation network: Temporal evolution of network topology and robustness from 2001 to 2016
Leonidas Siozos-Rousoulis, Dimitri Robert, Wouter Verbeke
The U.S. air transportation network (ATN) is critical to the mobility and the functioning of the United States. It is thus necessary to ensure that it is well-connected, efficient,…
Autoencoders for strategic decision support
Sam Verboven, Jeroen Berrevoets, Chris Wuytens +2
In the majority of executive domains, a notion of normality is involved in most strategic decisions. However, few data-driven tools that support strategic decision-making are avail…
Learning to rank for uplift modeling
Floris Devriendt, Tias Guns, Wouter Verbeke
Uplift modeling has effectively been used in fields such as marketing and customer retention, to target those customers that are most likely to respond due to the campaign or treat…
Social Network Analytics for Churn Prediction in Telco: Model Building, Evaluation and Network Architecture
María Óskarsdóttir, Cristián Bravo, Wouter Verbeke +3
Social network analytics methods are being used in the telecommunication industry to predict customer churn with great success. In particular it has been shown that relational lear…
A Comparative Study of Social Network Classifiers for Predicting Churn in the Telecommunication Industry
Maria Óskarsdóttir, Cristián Bravo, Wouter Verbeke +3
Relational learning in networked data has been shown to be effective in a number of studies. Relational learners, composed of relational classifiers and collective inference method…