93 citations · 192 across the 8 of their papers we have counts for
11 papers
Data driven value-at-risk forecasting using a SVR-GARCH-KDE hybrid
Marius Lux, Wolfgang Karl Härdle, Stefan Lessmann
Appropriate risk management is crucial to ensure the competitiveness of financial institutions and the stability of the economy. One widely used financial risk measure is Value-at-…
Improving Crime Count Forecasts Using Twitter and Taxi Data
Lara Vomfell, Wolfgang Karl Härdle, Stefan Lessmann
Crime prediction is crucial to criminal justice decision makers and efforts to prevent crime. The paper evaluates the explanatory and predictive value of human activity patterns de…
Conditional Wasserstein GAN-based Oversampling of Tabular Data for Imbalanced Learning
Justin Engelmann, Stefan Lessmann
Class imbalance is a common problem in supervised learning and impedes the predictive performance of classification models. Popular countermeasures include oversampling the minorit…
Response Transformation and Profit Decomposition for Revenue Uplift Modeling
Robin M. Gubela, Stefan Lessmann, Szymon Jaroszewicz
Uplift models support decision-making in marketing campaign planning. Estimating the causal effect of a marketing treatment, an uplift model facilitates targeting communication to…
Affordable Uplift: Supervised Randomization in Controlled Experiments
Johannes Haupt, Daniel Jacob, Robin M. Gubela +1
Customer scoring models are the core of scalable direct marketing. Uplift models provide an estimate of the incremental benefit from a treatment that is used for operational decisi…
Churn Prediction with Sequential Data and Deep Neural Networks. A Comparative Analysis
C. Gary Mena, Arno De Caigny, Kristof Coussement +2
Off-the-shelf machine learning algorithms for prediction such as regularized logistic regression cannot exploit the information of time-varying features without previously using an…