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Georg Krempl
Georg Krempl
Information and Computing Sciences, Utrecht University, The Netherlands
Geverifieerd e-mailadres voor uu.nl - Homepage
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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
3302014
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
502015
Drift mining in data: A framework for addressing drift in classification
V Hofer, G Krempl
Computational Statistics & Data Analysis 57 (1), 377-391, 2013
462013
The Algorithm APT to Classify in Concurrence of Latency and Drift.
G Krempl
IDA, 222-233, 2011
432011
Classification in presence of drift and latency
G Krempl, V Hofer
2011 IEEE 11th International Conference on Data Mining Workshops, 596-603, 2011
322011
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
292013
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
282016
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
272017
Probabilistic active learning in datastreams
D Kottke, G Krempl, M Spiliopoulou
Advances in Intelligent Data Analysis XIV: 14th International Symposium, IDA …, 2015
222015
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
212014
I. ˇZliobaite, D
G Krempl
Brzezinski, E. Hüllermeier, M. Last, V. Lemaire, T. Noack, A. Shaker, S …, 2014
202014
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
152011
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
142021
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
122021
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
102015
H¨ ullermeier
G Krempl, I Zliobaite, D Brzezinski
E., Last, M., Lemaire, V., Noack, T., Shaker, A., Sievi, S., Spiliopoulou, M …, 2014
102014
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
92015
Clustering-based optimised probabilistic active learning (COPAL)
G Krempl, TC Ha, M Spiliopoulou
Discovery Science: 18th International Conference, DS 2015, Banff, AB, Canada …, 2015
82015
Brzezi nski
G Krempl, I Žliobaite
D., Hüllermeier, E., Last, M., Lemaire, V., Noack, T., Shaker, A., Sievi, S …, 2014
82014
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
62022
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Artikelen 1–20