Solving Imbalanced Classification Problems with Support Vector Machines. - Stefan Lessmann (IC-AI, 2004)

Empirical comparison and evaluation of classifier performance for data mining in customer relationship management. - Sven F. Crone; Stefan Lessmann; Robert Stahlbock (IJCNN, 2004)

Optimizing Hyperparameters of Support Vector Machines by Genetic Algorithms. - Stefan Lessmann; Robert Stahlbock; Sven F. Crone (IC-AI, 2005)

Evolutionary Neural Classification Approaches for Strategic and Operational Decision Support in Retail Store Planning. - Robert Stahlbock; Stefan Lessmann; Sven F. Crone (IC-AI, 2005)

Genetically Constructed Kernels for Support Vector Machines. - Stefan Lessmann; Robert Stahlbock; Sven F. Crone (OR, 2005)

Parameter Sensitivity of Support Vector Regression and Neural Networks for Forecasting. - Sven F. Crone; Stefan Lessmann; Swantje Pietsch (DMIN, 2006)

Forecasting with Computational Intelligence - An Evaluation of Support Vector Regression and Artificial Neural Networks for Time Series Prediction. - Sven F. Crone; Stefan Lessmann; Swantje Pietsch (IJCNN, 2006)

An Evaluation of Discrete Support Vector Machines for Cost-Sensitive Learning. - Stefan Lessmann; Sven F. Crone; Robert Stahlbock (IJCNN, 2006)

Genetic Algorithms for Support Vector Machine Model Selection. - Stefan Lessmann; Robert Stahlbock; Sven F. Crone (IJCNN, 2006)

The impact of preprocessing on data mining: An evaluation of classifier sensitivity in direct marketing. - Sven F. Crone; Stefan Lessmann; Robert Stahlbock (Eur. J. Oper. Res., 2006)

A Novel Approach to Construct Discrete Support Vector Machine Classifiers. - Marco Caserta; Stefan Lessmann; Stefan Voß 001 (GfKl, 2008)

A Case Study of Core Vector Machines in Corporate Data Mining. - Stefan Lessmann; Ning Li; Stefan Voß 001 (HICSS, 2008)

Crowdsourcing: Systematisierung praktischer Ausprägungen und verwandter Konzepte. - Nicole Martin; Stefan Lessmann; Stefan Voß 001 (Multikonferenz Wirtschaftsinformatik, 2008)

Benchmarking Classification Models for Software Defect Prediction: A Proposed Framework and Novel Findings. - Stefan Lessmann; Bart Baesens; Christophe Mues; Swantje Pietsch (IEEE Trans. Software Eng., 2008)

Feature Selection in Marketing Applications. - Stefan Lessmann; Stefan Voß 001 (ADMA, 2009)

A Case Study of Random Forest in Predictive Data Mining. - Sebastian Schüller; Stefan Lessmann; Stefan Voß 001 (Wirtschaftsinformatik (2), 2009)

Identifying winners of competitive events: A SVM-based classification model for horserace prediction. - Stefan Lessmann; Ming-Chien Sung; Johnnie E. V. Johnson (Eur. J. Oper. Res., 2009)

A reference model for customer-centric data mining with support vector machines. - Stefan Lessmann; Stefan Voß 001 (Eur. J. Oper. Res., 2009)

Kostensensitive Klassifikation mit Random Forest. - Stefan Lessmann; Sebastian Schüller; Stefan Voß 001 (HMD Prax. Wirtsch., 2009)

Decision Support in Car Leasing: a Forecasting Model for Residual Value Estimation. - Stefan Lessmann; Mariana Listiani; Stefan Voß 001 (ICIS, 2010)

Customer-Centric Decision Support. - Stefan Lessmann; Stefan Voß 001 (Bus. Inf. Syst. Eng., 2010)

Data Mining and Information Systems: Quo Vadis? - Robert Stahlbock; Stefan Lessmann; Sven F. Crone (Data Mining, 2010)

Support of Managerial Decision Making by Transductive Learning. - Hubertus Brandner; Stefan Lessmann; Stefan Voß 001 (Wirtschaftsinformatik, 2011)

Tuning metaheuristics: A data mining based approach for particle swarm optimization. - Stefan Lessmann; Marco Caserta; Idel Montalvo Arango (Expert Syst. Appl., 2011)

Towards a methodology for measuring the true degree of efficiency in a speculative market. - Stefan Lessmann; Ming-Chien Sung; Johnnie E. V. Johnson (J. Oper. Res. Soc., 2011)

A new methodology for generating and combining statistical forecasting models to enhance competitive event prediction. - Stefan Lessmann; Ming-Chien Sung; Johnnie E. V. Johnson; Tiejun Ma (Eur. J. Oper. Res., 2012)

Save the best for last? The treatment of dominant predictors in financial forecasting. - Ming-Chien Sung; Stefan Lessmann (Expert Syst. Appl., 2012)

Modelling Mismatch In Predictive Analytics: A Case Study Illustration And Possible Remedy. - Stefan Lessmann (ECIS, 2013)

A memetic approach to construct transductive discrete support vector machines. - Hubertus Brandner; Stefan Lessmann; Stefan Voß 001 (Eur. J. Oper. Res., 2013)

Maximize What Matters: Predicting Customer Churn With Decision-Centric Ensemble Selection. - Annika Baumann; Stefan Lessmann; Kristof Coussement; Koen W. De Bock (ECIS, 2015)

Sales Forecasting with Partial Recurrent Neural Networks: Empirical Insights and Benchmarking Results. - Moritz Müller-Navarra; Stefan Lessmann; Stefan Voss 001 (HICSS, 2015)

Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research. - Stefan Lessmann; Bart Baesens; Hsin-Vonn Seow; Lyn C. Thomas (Eur. J. Oper. Res., 2015)

Twitter and the Political Landscape - a Graph Analysis of German Politicians. - Annika Baumann; Benjamin Fabian; Stefan Lessmann; Lars Holzberg (ECIS, 2016)

Data-Driven Product returns Prediction: a Cloud-based Ensemble Selection Approach. - Leonard Heilig; Julien Hofer; Stefan Lessmann; Stefan Voß 001 (ECIS, 2016)

E-Mail Tracking: Status Quo and Novel Countermeasures. - Benedict Bender; Benjamin Fabian; Stefan Lessmann; Johannes Haupt (ICIS, 2016)

Bridging the divide in financial market forecasting: machine learners vs. financial economists. - Ming-Wei Hsu; Stefan Lessmann; Ming-Chien Sung; Tiejun Ma; Johnnie E. V. Johnson (Expert Syst. Appl., 2016)

To Phub or not to Phub: Understanding off-Task Smartphone Usage and its Consequences in the Academic Environment. - Olga Abramova; Annika Baumann; Hanna Krasnova; Stefan Lessmann (ECIS, 2017)

Revenue Uplift Modeling. - Robin Marco Gubela; Stefan Lessmann; Johannes Haupt; Annika Baumann; Tillmann Radmer; Fabian Gebert (ICIS, 2017)

A comparative analysis of data preparation algorithms for customer churn prediction: A case study in the telecommunication industry. - Kristof Coussement; Stefan Lessmann; Geert Verstraeten (Decis. Support Syst., 2017)

Extreme learning machines for credit scoring: An empirical evaluation. - Artem Bequé; Stefan Lessmann (Expert Syst. Appl., 2017)

Approaches for credit scorecard calibration: An empirical analysis. - Artem Bequé; Kristof Coussement; Ross W. Gayler; Stefan Lessmann (Knowl. Based Syst., 2017)

Track and Treat - Usage of E-Mail Tracking for Newsletter Individualization. - Benedict Bender; Benjamin Fabian; Johannes Haupt; Stefan Lessmann (ECIS, 2018)

Profit-Oriented Feature Selection in Credit Scoring Applications. - Nikita Kozodoi; Stefan Lessmann; Bart Baesens; Konstantinos Papakonstantinou (OR, 2018)

Improving crime count forecasts using Twitter and taxi data. - Lara Vomfell; Wolfgang Karl Härdle; Stefan Lessmann (Decis. Support Syst., 2018)

Robust identification of email tracking: A machine learning approach. - Johannes Haupt; Benedict Bender; Benjamin Fabian; Stefan Lessmann (Eur. J. Oper. Res., 2018)

Changing perspectives: Using graph metrics to predict purchase probabilities. - Annika Baumann; Johannes Haupt; Fabian Gebert; Stefan Lessmann (Expert Syst. Appl., 2018)

Metaheuristics and Classifier Ensembles. - Ringolf Thomschke; Stefan Voß 001; Stefan Lessmann (Business and Consumer Analytics: New Ideas, 2019)

Affordable Uplift: Supervised Randomization in Controlled Experiments. - Johannes Haupt; Daniel Jacob; Robin Marco Gubela; Stefan Lessmann (ICIS, 2019)

Shallow Self-learning for Reject Inference in Credit Scoring. - Nikita Kozodoi; Panagiotis Katsas; Stefan Lessmann; Luís Moreira-Matias; Konstantinos Papakonstantinou (ECML/PKDD (3), 2019)

The Price of Privacy - An Evaluation of the Economic Value of Collecting Clickstream Data. - Annika Baumann; Johannes Haupt; Fabian Gebert; Stefan Lessmann (Bus. Inf. Syst. Eng., 2019)

Evaluating software defect prediction performance: an updated benchmarking study. - Libo Li; Stefan Lessmann; Bart Baesens (CoRR, 2019)

Churn Prediction with Sequential Data and Deep Neural Networks. A Comparative Analysis. - C. Gary Mena; Arno De Caigny; Kristof Coussement; Koen W. De Bock; Stefan Lessmann (CoRR, 2019)

A multi-objective approach for profit-driven feature selection in credit scoring. - Nikita Kozodoi; Stefan Lessmann; Konstantinos Papakonstantinou; Yiannis Gatsoulis; Bart Baesens (Decis. Support Syst., 2019)

Conversion Uplift in E-Commerce: A Systematic Benchmark of Modeling Strategies. - Robin Marco Gubela; Artem Bequé; Stefan Lessmann; Fabian Gebert (Int. J. Inf. Technol. Decis. Mak., 2019)

A conceptual framework for the adoption of big data analytics by e-commerce startups: a case-based approach. - Abhishek Behl; Pankaj Dutta; Stefan Lessmann; Yogesh K. Dwivedi; Samarjit Kar (Inf. Syst. E Bus. Manag., 2019)

Interpretable Multiple Treatment Revenue Uplift Modeling. - Robin Marco Gubela; Stefan Lessmann (AMCIS, 2020)

Uplift Forest for Multiple Treatments and Continuous Outcomes. - Robin Marco Gubela; Stefan Lessmann (ICIS, 2020)

Multi-objective Particle Swarm Optimization for Feature Selection in Credit Scoring. - Nikita Kozodoi; Stefan Lessmann (MIDAS@PKDD/ECML, 2020)

To Use or not to Use: the Relationship between Personality Traits and Instagram Usage. - Carlos Jennewein; Annika Baumann; Stefan Lessmann (Wirtschaftsinformatik (Zentrale Tracks), 2020)

Data driven value-at-risk forecasting using a SVR-GARCH-KDE hybrid. - Marius Lux; Wolfgang Karl Härdle; Stefan Lessmann (Comput. Stat., 2020)

Deep learning for detecting financial statement fraud. - Patricia Craja; Alisa Kim; Stefan Lessmann (Decis. Support Syst., 2020)

Antisocial online behavior detection using deep learning. - Elizaveta Zinovyeva; Wolfgang Karl Härdle; Stefan Lessmann (Decis. Support Syst., 2020)

Cost-sensitive business failure prediction when misclassification costs are uncertain: A heterogeneous ensemble selection approach. - Koen W. De Bock; Kristof Coussement; Stefan Lessmann (Eur. J. Oper. Res., 2020)

Response transformation and profit decomposition for revenue uplift modeling. - Robin Marco Gubela; Stefan Lessmann; Szymon Jaroszewicz (Eur. J. Oper. Res., 2020)

Can deep learning predict risky retail investors? A case study in financial risk behavior forecasting. - Alisa Kim; Yaodong Yang 001; Stefan Lessmann; Tiejun Ma; Ming-Chien Sung; Johnnie E. V. Johnson (Eur. J. Oper. Res., 2020)

Predicting online shopping behaviour from clickstream data using deep learning. - Dennis Koehn; Stefan Lessmann; Markus Schaal (Expert Syst. Appl., 2020)

Personalization in E-Grocery: Top-N versus Top-k Rankings. - Franziska Scherpinski; Stefan Lessmann (CoRR, 2021)

Leveraging Image-based Generative Adversarial Networks for Time Series Generation. - Justin Hellermann; Stefan Lessmann (CoRR, 2021)

Uplift modeling with value-driven evaluation metrics. - Robin Marco Gubela; Stefan Lessmann (Decis. Support Syst., 2021)

Conditional Wasserstein GAN-based oversampling of tabular data for imbalanced learning. - Justin Engelmann; Stefan Lessmann (Expert Syst. Appl., 2021)

Enterprise-grade protection against e-mail tracking. - Benjamin Fabian; Benedict Bender; Ben Hesseldieck; Johannes Haupt; Stefan Lessmann (Inf. Syst., 2021)

Targeting customers for profit: An ensemble learning framework to support marketing decision-making. - Stefan Lessmann; Johannes Haupt; Kristof Coussement; Koen W. De Bock (Inf. Sci., 2021)

A Hybrid Approach of Machine Learning and Lexicons to Sentiment Analysis: Enhanced Insights from Twitter Data of Natural Disasters. - Shalak Mendon; Pankaj Dutta; Abhishek Behl; Stefan Lessmann (Inf. Syst. Frontiers, 2021)

Modeling Irregular Time Series with Continuous Recurrent Units. - Mona Schirmer; Mazin Eltayeb; Stefan Lessmann; Maja Rudolph (ICML, 2022)

A Data-driven Case-based Reasoning in Bankruptcy Prediction. - Wei Li; Wolfgang Karl Härdle; Stefan Lessmann (CoRR, 2022)

Targeting customers under response-dependent costs. - Johannes Haupt; Stefan Lessmann (Eur. J. Oper. Res., 2022)

Fairness in credit scoring: Assessment, implementation and profit implications. - Nikita Kozodoi; Johannes Jacob; Stefan Lessmann (Eur. J. Oper. Res., 2022)

Usage Continuance in Software-as-a-Service. - Elias Baumann; Jana Kern; Stefan Lessmann (Inf. Syst. Frontiers, 2022)

Deep learning for survival and competing risk modelling. - Gabriel Blumenstock; Stefan Lessmann; Hsin-Vonn Seow (J. Oper. Res. Soc., 2022)

Fair Models in Credit: Intersectional Discrimination and the Amplification of Inequity. - Savina Dine Kim; Stefan Lessmann; Galina Andreeva; Michael Rovatsos (CoRR, 2023)

Forecasting Cryptocurrency Prices Using Deep Learning: Integrating Financial, Blockchain, and Text Data. - Vincent Gurgul; Stefan Lessmann; Wolfgang Karl Härdle (CoRR, 2023)

The impact of heteroskedasticity on uplift modeling. - Björn Bokelmann; Stefan Lessmann (CoRR, 2023)

Data-driven support for policy and decision-making in university research management: A case study from Germany. - Alona Zharova; Wolfgang Karl Härdle; Stefan Lessmann (Eur. J. Oper. Res., 2023)

Optimizing Household Energy Use: An Activity-based Recommendation System for Reducing CO2 Emissions. - Alona Zharova; Laura Löschmann; Stefan Lessmann (Wirtschaftsinformatik, 2024)

Leveraging Zero-Shot Prompting for Efficient Language Model Distillation. - Lukas Vöge; Vincent Gurgul; Stefan Lessmann (CoRR, 2024)

How much do we really know about Structure Learning from i.i.d. Data? Interpretable, multi-dimensional Performance Indicator for Causal Discovery. - Georg Velev; Stefan Lessmann (CoRR, 2024)

Energy Price Modelling: A Comparative Evaluation of four Generations of Forecasting Methods. - Alexandru-Victor Andrei; Georg Velev; Filip-Mihai Toma; Daniel Traian Pele; Stefan Lessmann (CoRR, 2024)

Leveraging AI and NLP for Bank Marketing: A Systematic Review and Gap Analysis. - Christopher Gerling; Stefan Lessmann (CoRR, 2024)

Uplift modeling with continuous treatments: A predict-then-optimize approach. - Simon De Vos; Christopher Bockel-Rickermann; Stefan Lessmann; Wouter Verbeke (CoRR, 2024)

Explainable AI for Operational Research: A defining framework, methods, applications, and a research agenda. - Koen W. De Bock; Kristof Coussement; Arno De Caigny; Roman Slowinski; Bart Baesens; Robert N. Boute; Tsan-Ming Choi; Dursun Delen; Mathias Kraus; Stefan Lessmann; Sebastián Maldonado; David Martens; et al. (Eur. J. Oper. Res., 2024)

Fx-spot predictions with state-of-the-art transformer and time embeddings. - Tizian Fischer; Marius Sterling; Stefan Lessmann (Expert Syst. Appl., 2024)

Improving uplift model evaluation on randomized controlled trial data. - Björn Bokelmann; Stefan Lessmann (Eur. J. Oper. Res., 2024)

Multiple Treatment Modeling for Target Marketing Campaigns: A Large-Scale Benchmark Study. - Robin Marco Gubela; Stefan Lessmann; Björn Stöcker (Inf. Syst. Frontiers, 2024)

Exploiting time-varying RFM measures for customer churn prediction with deep neural networks. - C. Gary Mena; Kristof Coussement; Koen W. De Bock; Arno De Caigny; Stefan Lessmann (Ann. Oper. Res., 2024)

The Deep Promotion Time Cure Model. - Victor Medina-Olivares; Stefan Lessmann; Nadja Klein (IEEE Trans. Neural Networks Learn. Syst., 2024)

Heteroscedasticity-aware stratified sampling to improve uplift modeling. - Björn Bokelmann; Stefan Lessmann (Eur. J. Oper. Res., 2025)

Fighting sampling bias: A framework for training and evaluating credit scoring models. - Nikita Kozodoi; Stefan Lessmann; Morteza Alamgir; Luís Moreira-Matias; Konstantinos Papakonstantinou (Eur. J. Oper. Res., 2025)

Multimodal Document Analytics for Banking Process Automation. - Christopher Gerling; Stefan Lessmann (Inf. Fusion, 2025)

In the beginning was the Word: LLM-VaR and LLM-ES. - Daniel Traian Pele; Vlad Bolovaneanu; Min-Bin Lin; Rui Ren; Andrei Theodor Ginavar; Bruno Spilak; Alexandru-Victor Andrei; Filip-Mihai Toma; Stefan Lessmann; Wolfgang Karl Härdle (Expert Syst. Appl., 2026)