| Open challenges for data stream mining research G Krempl, I Žliobaite, D Brzeziński, E Hüllermeier, M Last, V Lemaire, ... ACM SIGKDD explorations newsletter 16 (1), 1-10, 2014 | 250 | 2014 |
| Optimised probabilistic active learning (OPAL) For fast, non-myopic, cost-sensitive active classification G Krempl, D Kottke, V Lemaire Machine Learning 100 (2-3), 449-476, 2015 | 38 | 2015 |
| The algorithm APT to classify in concurrence of latency and drift G Krempl International Symposium on Intelligent Data Analysis, 222-233, 2011 | 34 | 2011 |
| Drift mining in data: A framework for addressing drift in classification V Hofer, G Krempl Computational Statistics & Data Analysis 57 (1), 377-391, 2013 | 30 | 2013 |
| Correcting the usage of the hoeffding inequality in stream mining P Matuszyk, G Krempl, M Spiliopoulou International Symposium on Intelligent Data Analysis, 298-309, 2013 | 24 | 2013 |
| Multi-class probabilistic active learning D Kottke, G Krempl, D Lang, J Teschner, M Spiliopoulou Proceedings of the Twenty-second European Conference on Artificial …, 2016 | 20 | 2016 |
| Z? liobaite, I G Krempl BrzeziÁski, D., Hüllermeier, E., Last, M., Lemaire, V., Noack, T., Shaker, A …, 2014 | 20 | 2014 |
| Classification in presence of drift and latency G Krempl, V Hofer 2011 IEEE 11th International Conference on Data Mining Workshops, 596-603, 2011 | 20 | 2011 |
| Online clustering of high-dimensional trajectories under concept drift G Krempl, ZF Siddiqui, M Spiliopoulou Joint European Conference on Machine Learning and Knowledge Discovery in …, 2011 | 15 | 2011 |
| Challenges of reliable, realistic and comparable active learning evaluation D Kottke, A Calma, D Huseljic, GM Krempl, B Sick Proceedings of the Workshop and Tutorial on Interactive Adaptive Learning, 2-14, 2017 | 14 | 2017 |
| Probabilistic active learning: Towards combining versatility, optimality and efficiency G Krempl, D Kottke, M Spiliopoulou International Conference on Discovery Science, 168-179, 2014 | 14 | 2014 |
| Probabilistic active learning in datastreams D Kottke, G Krempl, M Spiliopoulou International Symposium on Intelligent Data Analysis, 145-157, 2015 | 13 | 2015 |
| How to Select Information That Matters: A Comparative Study on Active Learning Strategies for Classification C Beyer, G Krempl, V Lemaire 15th ACM International Conference on Knowledge Technologies and Data-Driven …, 2015 | 7 | 2015 |
| Predicting the post-treatment recovery of patients suffering from traumatic brain injury (TBI) ZF Siddiqui, G Krempl, M Spiliopoulou, JM Peña, N Paul, F Maestu Brain informatics 2 (1), 33-44, 2015 | 6 | 2015 |
| Probabilistic active learning for active class selection D Kottke, G Krempl, M Stecklina, CS von Rekowski, T Sabsch, TP Minh, ... Proc. of the NIPS Workshop on the Future of Interactive Learning Machines, 2016 | 5 | 2016 |
| Clustering-based optimised probabilistic active learning (COPAL) G Krempl, TC Ha, M Spiliopoulou International Conference on Discovery Science, 101-115, 2015 | 5 | 2015 |
| Probabilistic Active Learning: A Short Proposition. G Krempl, D Kottke, M Spiliopoulou ECAI, 1049-1050, 2014 | 5 | 2014 |
| ¿ liobaite I, Brzezinski D, Hüllermeier E, Last M, Lemaire V, Noack T, Shaker A, Sievi S, Spiliopoulou M, Stefanowski J (2014) Open challenges for data stream mining research G Krempl SIGKDD Explor 16 (1), 1-10, 0 | 4 | |
| Frontiers in Artificial Intelligence and Applications H Fujita, E Herrera-Viedma IOS Press: Amsterdam, The Netherlands 303, 157-170, 2018 | 3 | 2018 |
| Partitioner trees: combining boosting and arbitrating G Krempl, V Hofer Workshop on Supervised and Unsupervised Ensemble Methods and their …, 2008 | 3 | 2008 |
Daniel KottkeResearch Assistant, Kassel UniversityVerified email at uni-kassel.de
