| Incremental learning with support vector machines S Ruping Proceedings 2001 IEEE international conference on data mining, 641-642, 2001 | 338 | 2001 |
| A review of machine learning for the optimization of production processes D Weichert, P Link, A Stoll, S Rüping, S Ihlenfeldt, S Wrobel The International Journal of Advanced Manufacturing Technology 104 (5), 1889 …, 2019 | 289 | 2019 |
| SVM classifier estimation from group probabilities S Rueping Proceedings of the 27th international conference on machine learning (ICML …, 2010 | 163 | 2010 |
| SVM kernels for time series analysis S Rüping Technical report, 2001 | 152 | 2001 |
| mySVM-manual S Ruping http://www-ai. cs. uni-dortmund. de/SOFTWARE/MYSVM/, 2000 | 151 | 2000 |
| Tight optimistic estimates for fast subgroup discovery H Grosskreutz, S Rüping, S Wrobel Joint European conference on machine learning and knowledge discovery in …, 2008 | 138 | 2008 |
| On subgroup discovery in numerical domains H Grosskreutz, S Rüping Data mining and knowledge discovery 19, 210-226, 2009 | 137 | 2009 |
| Learning interpretable models S Rüping | 136 | 2006 |
| Advanced sensing and human activity recognition in early intervention and rehabilitation of elderly people L Schrader, A Vargas Toro, S Konietzny, S Rüping, B Schäpers, ... Journal of Population Ageing 13, 139-165, 2020 | 87 | 2020 |
| E2mc: Improving emergency management service practice through social media and crowdsourcing analysis in near real time C Havas, B Resch, C Francalanci, B Pernici, G Scalia, ... Sensors 17 (12), 2766, 2017 | 85 | 2017 |
| Concept Drift and the Importance of Example. R Klinkenberg, S Rüping Text mining, 55-78, 2003 | 67 | 2003 |
| Inspect, understand, overcome: A survey of practical methods for ai safety S Houben, S Abrecht, M Akila, A Bär, F Brockherde, P Feifel, ... Deep Neural Networks and Data for Automated Driving: Robustness, Uncertainty …, 2022 | 58 | 2022 |
| Data science in healthcare: Benefits, challenges and opportunities Z Abedjan, N Boujemaa, S Campbell, P Casla, S Chatterjea, S Consoli, ... Data Science for Healthcare: Methodologies and Applications, 3-38, 2019 | 46 | 2019 |
| Maschinelles Lernen. Eine Analyse zu Kompetenzen, Forschung und Anwendung I Döbel, M Leis, M Molina Vogelsang, D Neustroev, H Petzka, A Riemer, ... Fraunhofer-Gesellschaft, 2018 | 46 | 2018 |
| Support vector machines and learning about time S Ruping, K Morik 2003 IEEE International Conference on Acoustics, Speech, and Signal …, 2003 | 46 | 2003 |
| Big data in medizin und gesundheitswesen S Rüping Bundesgesundheitsblatt-Gesundheitsforschung-Gesundheitsschutz 58 (8), 794-798, 2015 | 43* | 2015 |
| Maschinelles Lernen. Eine Analyse zu Kompetenzen I Döbel, M Leis, MM Vogelsang, D Neustroev, H Petzka, A Riemer, ... Forschung und Anwendung, 2018 | 40 | 2018 |
| A simple method for estimating conditional probabilities for svms S Rüping Technical report, 2004 | 39 | 2004 |
| On integrating data mining into business processes D Wegener, S Rüping Business Information Systems: 13th International Conference, BIS 2010 …, 2010 | 37 | 2010 |
| Ranking interesting subgroups S Rueping Proceedings of the 26th annual international conference on machine learning …, 2009 | 36 | 2009 |
