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Stefan Lessmann
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- affiliation: HU Berlin, Germany
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2020 – today
- 2024
- [j45]C. Gary Mena, Kristof Coussement, Koen W. De Bock, Arno De Caigny, Stefan Lessmann
:
Exploiting time-varying RFM measures for customer churn prediction with deep neural networks. Ann. Oper. Res. 339(1-2): 765-787 (2024) - [j44]Björn Bokelmann
Improving uplift model evaluation on randomized controlled trial data. Eur. J. Oper. Res. 313(2): 691-707 (2024) - [j43]Koen W. De Bock
Explainable AI for Operational Research: A defining framework, methods, applications, and a research agenda. Eur. J. Oper. Res. 317(2): 249-272 (2024) - [j42]Tizian Fischer
Fx-spot predictions with state-of-the-art transformer and time embeddings. Expert Syst. Appl. 249: 123538 (2024) - [j41]Robin Marco Gubela
Multiple Treatment Modeling for Target Marketing Campaigns: A Large-Scale Benchmark Study. Inf. Syst. Frontiers 26(3): 875-898 (2024) - [i21]Lukas Vöge, Vincent Gurgul, Stefan Lessmann:
Leveraging Zero-Shot Prompting for Efficient Language Model Distillation. CoRR abs/2403.15886 (2024) - [i20]Nikita Kozodoi, Stefan Lessmann, Morteza Alamgir, Luís Moreira-Matias, Konstantinos Papakonstantinou:
Fighting Sampling Bias: A Framework for Training and Evaluating Credit Scoring Models. CoRR abs/2407.13009 (2024) - [i19]Georg Velev, Stefan Lessmann:
How much do we really know about Structure Learning from i.i.d. Data? Interpretable, multi-dimensional Performance Indicator for Causal Discovery. CoRR abs/2409.19377 (2024) - 2023
- [j40]Alona Zharova
Data-driven support for policy and decision-making in university research management: A case study from Germany. Eur. J. Oper. Res. 308(1): 353-368 (2023) - [i18]Victor Medina-Olivares
The Deep Promotion Time Cure Model. CoRR abs/2305.11575 (2023) - [i17]Christopher Gerling, Stefan Lessmann:
Multimodal Document Analytics for Banking Process Automation. CoRR abs/2307.11845 (2023) - [i16]Savina Dine Kim, Stefan Lessmann, Galina Andreeva, Michael Rovatsos:
Fair Models in Credit: Intersectional Discrimination and the Amplification of Inequity. CoRR abs/2308.02680 (2023) - [i15]Vincent Gurgul, Stefan Lessmann, Wolfgang Karl Härdle:
Forecasting Cryptocurrency Prices Using Deep Learning: Integrating Financial, Blockchain, and Text Data. CoRR abs/2311.14759 (2023) - [i14]Björn Bokelmann, Stefan Lessmann:
The impact of heteroskedasticity on uplift modeling. CoRR abs/2312.05234 (2023) - 2022
- [j39]Johannes Haupt, Stefan Lessmann
Targeting customers under response-dependent costs. Eur. J. Oper. Res. 297(1): 369-379 (2022) - [j38]Nikita Kozodoi
Fairness in credit scoring: Assessment, implementation and profit implications. Eur. J. Oper. Res. 297(3): 1083-1094 (2022) - [j37]Elias Baumann, Jana Kern, Stefan Lessmann
Usage Continuance in Software-as-a-Service. Inf. Syst. Frontiers 24(1): 149-176 (2022) - [j36]Gabriel Blumenstock, Stefan Lessmann
Deep learning for survival and competing risk modelling. J. Oper. Res. Soc. 73(1): 26-38 (2022) - [c32]Mona Schirmer, Mazin Eltayeb, Stefan Lessmann
Modeling Irregular Time Series with Continuous Recurrent Units. ICML 2022: 19388-19405 - [i13]Wei Li, Wolfgang Karl Härdle, Stefan Lessmann:
A Data-driven Case-based Reasoning in Bankruptcy Prediction. CoRR abs/2211.00921 (2022) - 2021
- [j35]Robin Marco Gubela, Stefan Lessmann
Uplift modeling with value-driven evaluation metrics. Decis. Support Syst. 150: 113648 (2021) - [j34]Justin Engelmann, Stefan Lessmann
Conditional Wasserstein GAN-based oversampling of tabular data for imbalanced learning. Expert Syst. Appl. 174: 114582 (2021) - [j33]Benjamin Fabian, Benedict Bender
Enterprise-grade protection against e-mail tracking. Inf. Syst. 97: 101702 (2021) - [j32]Stefan Lessmann
Targeting customers for profit: An ensemble learning framework to support marketing decision-making. Inf. Sci. 557: 286-301 (2021) - [j31]Shalak Mendon, Pankaj Dutta
A Hybrid Approach of Machine Learning and Lexicons to Sentiment Analysis: Enhanced Insights from Twitter Data of Natural Disasters. Inf. Syst. Frontiers 23(5): 1145-1168 (2021) - [i12]Robin Marco Gubela, Stefan Lessmann:
Interpretable Multiple Treatment Revenue Uplift Modeling. CoRR abs/2101.03336 (2021) - [i11]Nikita Kozodoi, Johannes Jacob, Stefan Lessmann:
Fairness in Credit Scoring: Assessment, Implementation and Profit Implications. CoRR abs/2103.01907 (2021) - [i10]Franziska Scherpinski, Stefan Lessmann:
Personalization in E-Grocery: Top-N versus Top-k Rankings. CoRR abs/2105.14599 (2021) - [i9]Mona Schirmer, Mazin Eltayeb, Stefan Lessmann, Maja Rudolph:
Modeling Irregular Time Series with Continuous Recurrent Units. CoRR abs/2111.11344 (2021) - [i8]Justin Hellermann, Stefan Lessmann:
Leveraging Image-based Generative Adversarial Networks for Time Series Generation. CoRR abs/2112.08060 (2021) - 2020
- [j30]Marius Lux, Wolfgang Karl Härdle
Data driven value-at-risk forecasting using a SVR-GARCH-KDE hybrid. Comput. Stat. 35(3): 947-981 (2020) - [j29]Elizaveta Zinovyeva, Wolfgang Karl Härdle, Stefan Lessmann
Antisocial online behavior detection using deep learning. Decis. Support Syst. 138: 113362 (2020) - [j28]Patricia Craja, Alisa Kim, Stefan Lessmann
Deep learning for detecting financial statement fraud. Decis. Support Syst. 139: 113421 (2020) - [j27]Alisa Kim, Yaodong Yang, Stefan Lessmann
Can deep learning predict risky retail investors? A case study in financial risk behavior forecasting. Eur. J. Oper. Res. 283(1): 217-234 (2020) - [j26]Robin Marco Gubela
Response transformation and profit decomposition for revenue uplift modeling. Eur. J. Oper. Res. 283(2): 647-661 (2020) - [j25]Koen W. De Bock, Kristof Coussement
Cost-sensitive business failure prediction when misclassification costs are uncertain: A heterogeneous ensemble selection approach. Eur. J. Oper. Res. 285(2): 612-630 (2020) - [j24]Dennis Koehn, Stefan Lessmann
Predicting online shopping behaviour from clickstream data using deep learning. Expert Syst. Appl. 150: 113342 (2020) - [c31]Robin Marco Gubela, Stefan Lessmann:
Interpretable Multiple Treatment Revenue Uplift Modeling. AMCIS 2020 - [c30]Robin Marco Gubela, Stefan Lessmann:
Uplift Forest for Multiple Treatments and Continuous Outcomes. ICIS 2020 - [c29]Nikita Kozodoi, Stefan Lessmann
Multi-objective Particle Swarm Optimization for Feature Selection in Credit Scoring. MIDAS@PKDD/ECML 2020: 68-76 - [c28]Carlos Jennewein, Annika Baumann, Stefan Lessmann
To Use or not to Use: the Relationship between Personality Traits and Instagram Usage. Wirtschaftsinformatik (Zentrale Tracks) 2020: 1561-1576 - [i7]Justin Engelmann, Stefan Lessmann:
Conditional Wasserstein GAN-based Oversampling of Tabular Data for Imbalanced Learning. CoRR abs/2008.09202 (2020)
2010 – 2019
- 2019
- [j23]Annika Baumann, Johannes Haupt
The Price of Privacy - An Evaluation of the Economic Value of Collecting Clickstream Data. Bus. Inf. Syst. Eng. 61(4): 413-431 (2019) - [j22]Nikita Kozodoi, Stefan Lessmann
A multi-objective approach for profit-driven feature selection in credit scoring. Decis. Support Syst. 120: 106-117 (2019) - [j21]Robin Marco Gubela
Conversion Uplift in E-Commerce: A Systematic Benchmark of Modeling Strategies. Int. J. Inf. Technol. Decis. Mak. 18(3): 747-791 (2019) - [j20]Abhishek Behl
A conceptual framework for the adoption of big data analytics by e-commerce startups: a case-based approach. Inf. Syst. E Bus. Manag. 17(2-4): 285-318 (2019) - [c27]Johannes Haupt, Daniel Jacob, Robin Marco Gubela, Stefan Lessmann:
Affordable Uplift: Supervised Randomization in Controlled Experiments. ICIS 2019 - [c26]Nikita Kozodoi, Panagiotis Katsas, Stefan Lessmann
Shallow Self-learning for Reject Inference in Credit Scoring. ECML/PKDD (3) 2019: 516-532 - [p2]Ringolf Thomschke, Stefan Voß, Stefan Lessmann:
Metaheuristics and Classifier Ensembles. Business and Consumer Analytics: New Ideas 2019: 733-779 - [i6]Libo Li, Stefan Lessmann, Bart Baesens:
Evaluating software defect prediction performance: an updated benchmarking study. CoRR abs/1901.01726 (2019) - [i5]Nikita Kozodoi, Panagiotis Katsas, Stefan Lessmann, Luís Moreira-Matias, Konstantinos Papakonstantinou:
Shallow Self-Learning for Reject Inference in Credit Scoring. CoRR abs/1909.06108 (2019) - [i4]C. Gary Mena, Arno De Caigny, Kristof Coussement, Koen W. De Bock, Stefan Lessmann:
Churn Prediction with Sequential Data and Deep Neural Networks. A Comparative Analysis. CoRR abs/1909.11114 (2019) - [i3]Johannes Haupt
Affordable Uplift: Supervised Randomization in Controlled Experiments. CoRR abs/1910.00393 (2019) - [i2]Robin Marco Gubela, Stefan Lessmann, Szymon Jaroszewicz:
Response Transformation and Profit Decomposition for Revenue Uplift Modeling. CoRR abs/1911.08729 (2019) - 2018
- [j19]Lara Vomfell, Wolfgang Karl Härdle
Improving crime count forecasts using Twitter and taxi data. Decis. Support Syst. 113: 73-85 (2018) - [j18]Johannes Haupt
Robust identification of email tracking: A machine learning approach. Eur. J. Oper. Res. 271(1): 341-356 (2018) - [j17]Annika Baumann, Johannes Haupt
Changing perspectives: Using graph metrics to predict purchase probabilities. Expert Syst. Appl. 94: 137-148 (2018) - [c25]Benedict Bender, Benjamin Fabian, Johannes Haupt, Stefan Lessmann:
Track and Treat - Usage of E-Mail Tracking for Newsletter Individualization. ECIS 2018: 59 - [c24]Nikita Kozodoi, Stefan Lessmann, Bart Baesens, Konstantinos Papakonstantinou:
Profit-Oriented Feature Selection in Credit Scoring Applications. OR 2018: 59-65 - [i1]Johannes Haupt, Benedict Bender, Benjamin Fabian, Stefan Lessmann:
Robust identification of email tracking: A machine learning approach. CoRR abs/1806.04033 (2018) - 2017
- [j16]Kristof Coussement
A comparative analysis of data preparation algorithms for customer churn prediction: A case study in the telecommunication industry. Decis. Support Syst. 95: 27-36 (2017) - [j15]Artem Bequé, Stefan Lessmann
Extreme learning machines for credit scoring: An empirical evaluation. Expert Syst. Appl. 86: 42-53 (2017) - [j14]Artem Bequé, Kristof Coussement
Approaches for credit scorecard calibration: An empirical analysis. Knowl. Based Syst. 134: 213-227 (2017) - [c23]Olga Abramova, Annika Baumann, Hanna Krasnova, Stefan Lessmann:
To Phub or not to Phub: Understanding off-Task Smartphone Usage and its Consequences in the Academic Environment. ECIS 2017: 127 - [c22]Robin Marco Gubela, Stefan Lessmann, Johannes Haupt, Annika Baumann, Tillmann Radmer, Fabian Gebert:
Revenue Uplift Modeling. ICIS 2017 - 2016
- [j13]Ming-Wei Hsu, Stefan Lessmann
Bridging the divide in financial market forecasting: machine learners vs. financial economists. Expert Syst. Appl. 61: 215-234 (2016) - [c21]Annika Baumann, Benjamin Fabian, Stefan Lessmann, Lars Holzberg:
Twitter and the Political Landscape - a Graph Analysis of German Politicians. ECIS 2016: Research Paper 132 - [c20]Leonard Heilig, Julien Hofer, Stefan Lessmann, Stefan Voß:
Data-Driven Product returns Prediction: a Cloud-based Ensemble Selection Approach. ECIS 2016: Research-in-Progress Paper 34 - [c19]Benedict Bender, Benjamin Fabian, Stefan Lessmann, Johannes Haupt:
E-Mail Tracking: Status Quo and Novel Countermeasures. ICIS 2016 - 2015
- [j12]Stefan Lessmann
Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research. Eur. J. Oper. Res. 247(1): 124-136 (2015) - [c18]Annika Baumann, Stefan Lessmann, Kristof Coussement, Koen W. De Bock:
Maximize What Matters: Predicting Customer Churn With Decision-Centric Ensemble Selection. ECIS 2015 - [c17]Moritz Müller-Navarra, Stefan Lessmann
Sales Forecasting with Partial Recurrent Neural Networks: Empirical Insights and Benchmarking Results. HICSS 2015: 1108-1116 - 2013
- [j11]Hubertus Brandner, Stefan Lessmann
A memetic approach to construct transductive discrete support vector machines. Eur. J. Oper. Res. 230(3): 581-595 (2013) - [c16]Stefan Lessmann:
Modelling Mismatch In Predictive Analytics: A Case Study Illustration And Possible Remedy. ECIS 2013: 104 - 2012
- [j10]Stefan Lessmann
A new methodology for generating and combining statistical forecasting models to enhance competitive event prediction. Eur. J. Oper. Res. 218(1): 163-174 (2012) - [j9]Ming-Chien Sung, Stefan Lessmann
Save the best for last? The treatment of dominant predictors in financial forecasting. Expert Syst. Appl. 39(15): 11898-11910 (2012) - 2011
- [j8]Stefan Lessmann
Tuning metaheuristics: A data mining based approach for particle swarm optimization. Expert Syst. Appl. 38(10): 12826-12838 (2011) - [j7]Stefan Lessmann
Towards a methodology for measuring the true degree of efficiency in a speculative market. J. Oper. Res. Soc. 62(12): 2120-2132 (2011) - [c15]Hubertus Brandner, Stefan Lessmann, Stefan Voß:
Support of Managerial Decision Making by Transductive Learning. Wirtschaftsinformatik 2011: 18 - 2010
- [j6]Stefan Lessmann, Stefan Voß:
Customer-Centric Decision Support. Bus. Inf. Syst. Eng. 2(2): 79-93 (2010) - [c14]Stefan Lessmann, Mariana Listiani, Stefan Voß:
Decision Support in Car Leasing: a Forecasting Model for Residual Value Estimation. ICIS 2010: 17 - [p1]Robert Stahlbock, Stefan Lessmann, Sven F. Crone
Data Mining and Information Systems: Quo Vadis? Data Mining 2010: 1-15 - [e5]Robert Stahlbock, Sven F. Crone
Data Mining - Special Issue in Annals of Information Systems. Annals of Information Systems 8, Springer 2010, ISBN 978-1-4419-1279-4 [contents]
2000 – 2009
- 2009
- [j5]Stefan Lessmann
Identifying winners of competitive events: A SVM-based classification model for horserace prediction. Eur. J. Oper. Res. 196(2): 569-577 (2009) - [j4]Stefan Lessmann
A reference model for customer-centric data mining with support vector machines. Eur. J. Oper. Res. 199(2): 520-530 (2009) - [j3]Stefan Lessmann, Sebastian Schüller, Stefan Voß:
Kostensensitive Klassifikation mit Random Forest. HMD Prax. Wirtsch. 268: 57-68 (2009) - [c13]Stefan Lessmann
Feature Selection in Marketing Applications. ADMA 2009: 200-208 - [c12]Sebastian Schüller, Stefan Lessmann, Stefan Voß:
A Case Study of Random Forest in Predictive Data Mining. Wirtschaftsinformatik (2) 2009: 319-328 - [e4]Robert Stahlbock, Sven F. Crone, Stefan Lessmann:
Proceedings of The 2009 International Conference on Data Mining, DMIN 2009, July 13-16, 2009, Las Vegas, USA. CSREA Press 2009, ISBN 1-60132-099-X [contents] - 2008
- [j2]Stefan Lessmann
Benchmarking Classification Models for Software Defect Prediction: A Proposed Framework and Novel Findings. IEEE Trans. Software Eng. 34(4): 485-496 (2008) - [c11]Marco Caserta, Stefan Lessmann, Stefan Voß:
A Novel Approach to Construct Discrete Support Vector Machine Classifiers. GfKl 2008: 115-125 - [c10]Stefan Lessmann
A Case Study of Core Vector Machines in Corporate Data Mining. HICSS 2008: 78 - [c9]Nicole Martin, Stefan Lessmann, Stefan Voß:
Crowdsourcing: Systematisierung praktischer Ausprägungen und verwandter Konzepte. Multikonferenz Wirtschaftsinformatik 2008 - [e3]Robert Stahlbock, Sven F. Crone, Stefan Lessmann:
Proceedings of The 2008 International Conference on Data Mining, DMIN 2008, July 14-17, 2008, Las Vegas, USA, 2 Volumes. CSREA Press 2008, ISBN 1-60132-062-0 [contents] - 2007
- [e2]Robert Stahlbock, Sven F. Crone, Stefan Lessmann:
Proceedings of the 2007 International Conference on Data Mining, DMIN 2007, June 25-28, 2007, Las Vegas, Nevada, USA. CSREA Press 2007, ISBN 1-60132-031-0 [contents] - 2006
- [j1]Sven F. Crone
The impact of preprocessing on data mining: An evaluation of classifier sensitivity in direct marketing. Eur. J. Oper. Res. 173(3): 781-800 (2006) - [c8]Sven F. Crone, Stefan Lessmann, Swantje Pietsch:
Parameter Sensitivity of Support Vector Regression and Neural Networks for Forecasting. DMIN 2006: 396-402 - [c7]Stefan Lessmann, Sven F. Crone, Robert Stahlbock:
An Evaluation of Discrete Support Vector Machines for Cost-Sensitive Learning. IJCNN 2006: 347-354 - [c6]Stefan Lessmann, Robert Stahlbock, Sven F. Crone:
Genetic Algorithms for Support Vector Machine Model Selection. IJCNN 2006: 3063-3069 - [c5]Sven F. Crone, Stefan Lessmann, Swantje Pietsch:
Forecasting with Computational Intelligence - An Evaluation of Support Vector Regression and Artificial Neural Networks for Time Series Prediction. IJCNN 2006: 3159-3166 - [e1]Sven F. Crone, Stefan Lessmann, Robert Stahlbock:
Proceedings of the 2006 International Conference on Data Mining, DMIN 2006, Las Vegas, Nevada, USA, June 26-29, 2006. CSREA Press 2006, ISBN 1-60132-004-3 [contents] - 2005
- [c4]Robert Stahlbock, Stefan Lessmann, Sven F. Crone:
Evolutionary Neural Classification Approaches for Strategic and Operational Decision Support in Retail Store Planning. IC-AI 2005: 60-66 - [c3]Stefan Lessmann, Robert Stahlbock, Sven F. Crone:
Optimizing Hyperparameters of Support Vector Machines by Genetic Algorithms. IC-AI 2005: 74-82 - [c2]Stefan Lessmann, Robert Stahlbock, Sven F. Crone
Genetically Constructed Kernels for Support Vector Machines. OR 2005: 257-262 - 2004
- [c1]Stefan Lessmann:
Solving Imbalanced Classification Problems with Support Vector Machines. IC-AI 2004: 214-220
Coauthor Index
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last updated on 2024-10-22 21:17 CEST by the dblp team
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