| 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 | 330 | 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 | 50 | 2015 |
| Drift mining in data: A framework for addressing drift in classification V Hofer, G Krempl Computational Statistics & Data Analysis 57 (1), 377-391, 2013 | 46 | 2013 |
| The Algorithm APT to Classify in Concurrence of Latency and Drift. G Krempl IDA, 222-233, 2011 | 43 | 2011 |
| Classification in presence of drift and latency G Krempl, V Hofer 2011 IEEE 11th International Conference on Data Mining Workshops, 596-603, 2011 | 32 | 2011 |
| Correcting the usage of the hoeffding inequality in stream mining P Matuszyk, G Krempl, M Spiliopoulou Advances in Intelligent Data Analysis XII: 12th International Symposium, IDA …, 2013 | 29 | 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 | 28 | 2016 |
| 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 | 27 | 2017 |
| Probabilistic active learning in datastreams D Kottke, G Krempl, M Spiliopoulou Advances in Intelligent Data Analysis XIV: 14th International Symposium, IDA …, 2015 | 22 | 2015 |
| Probabilistic active learning: Towards combining versatility, optimality and efficiency G Krempl, D Kottke, M Spiliopoulou Discovery Science: 17th International Conference, DS 2014, Bled, Slovenia …, 2014 | 21 | 2014 |
| I. ˇZliobaite, D G Krempl Brzezinski, E. Hüllermeier, M. Last, V. Lemaire, T. Noack, A. Shaker, S …, 2014 | 20 | 2014 |
| Online clustering of high-dimensional trajectories under concept drift G Krempl, ZF Siddiqui, M Spiliopoulou Machine Learning and Knowledge Discovery in Databases: European Conference …, 2011 | 15 | 2011 |
| Toward optimal probabilistic active learning using a Bayesian approach D Kottke, M Herde, C Sandrock, D Huseljic, G Krempl, B Sick Machine Learning 110 (6), 1199-1231, 2021 | 14 | 2021 |
| Probabilistic active learning for active class selection D Kottke, G Krempl, M Stecklina, CS von Rekowski, T Sabsch, TP Minh, ... arXiv preprint arXiv:2108.03891, 2021 | 12 | 2021 |
| Predicting the post-treatment recovery of patients suffering from traumatic brain injury (TBI) ZF Siddiqui, G Krempl, M Spiliopoulou, JM Pena, N Paul, F Maestu Brain informatics 2 (1), 33-44, 2015 | 10 | 2015 |
| H¨ ullermeier G Krempl, I Zliobaite, D Brzezinski E., Last, M., Lemaire, V., Noack, T., Shaker, A., Sievi, S., Spiliopoulou, M …, 2014 | 10 | 2014 |
| 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 | 9 | 2015 |
| Clustering-based optimised probabilistic active learning (COPAL) G Krempl, TC Ha, M Spiliopoulou Discovery Science: 18th International Conference, DS 2015, Banff, AB, Canada …, 2015 | 8 | 2015 |
| Brzezi nski G Krempl, I Žliobaite D., Hüllermeier, E., Last, M., Lemaire, V., Noack, T., Shaker, A., Sievi, S …, 2014 | 8 | 2014 |
| Stream-based active learning for sliding windows under the influence of verification latency T Pham, D Kottke, G Krempl, B Sick Machine Learning, 1-26, 2022 | 6 | 2022 |
Daniel KottkeResearcher, Kassel UniversityGeverifieerd e-mailadres voor uni-kassel.de
