| 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 | 357 | 2014 |
| On-line elimination of local redundancies in evolving fuzzy systems E Lughofer, JL Bouchot, A Shaker Evolving Systems 2, 165-187, 2011 | 120 | 2011 |
| IBLStreams: a system for instance-based classification and regression on data streams A Shaker, E Hüllermeier Evolving Systems 3, 235-249, 2012 | 91 | 2012 |
| Self-adaptive and local strategies for a smooth treatment of drifts in data streams A Shaker, E Lughofer Evolving Systems 5, 239-257, 2014 | 72 | 2014 |
| Recovery analysis for adaptive learning from non-stationary data streams: Experimental design and case study A Shaker, E Hüllermeier Neurocomputing 150, 250-264, 2015 | 50 | 2015 |
| Evolving fuzzy pattern trees for binary classification on data streams A Shaker, R Senge, E Hüllermeier Information Sciences 220, 34-45, 2013 | 45 | 2013 |
| SciPlore Xtract: extracting titles from scientific PDF documents by analyzing style information (Font Size) J Beel, B Gipp, A Shaker, N Friedrich Research and Advanced Technology for Digital Libraries: 14th European …, 2010 | 37 | 2010 |
| Metabags: Bagged meta-decision trees for regression J Khiari, L Moreira-Matias, A Shaker, B Ženko, S Džeroski Machine Learning and Knowledge Discovery in Databases: European Conference …, 2019 | 20 | 2019 |
| Instance-based classification and regression on data streams A Shaker, E Hüllermeier Learning in non-stationary environments: methods and applications, 185-201, 2012 | 18 | 2012 |
| Measuring the discrepancy between conditional distributions: Methods, properties and applications S Yu, A Shaker, F Alesiani, JC Principe Proceedings of the Twenty-Ninth International Joint Conference on Artificial …, 2020 | 14 | 2020 |
| Imprecise matching of requirements specifications for software services using fuzzy logic MC Platenius, A Shaker, M Becker, E Huellermeier, W Schaefer IEEE Transactions on Software Engineering 43 (8), 739-759, 2016 | 12 | 2016 |
| Survival analysis on data streams: Analyzing temporal events in dynamically changing environments A Shaker, E Hüllermeier International Journal of Applied Mathematics and Computer Science 24 (1 …, 2014 | 11 | 2014 |
| Efficient and scalable multi-task regression on massive number of tasks X He, F Alesiani, A Shaker Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 3763-3770, 2019 | 9 | 2019 |
| Resolving global and local drifts in data stream regression using evolving rule-based models A Shaker, E Lughofer 2013 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS), 9-16, 2013 | 8 | 2013 |
| Recovery analysis for adaptive learning from non-stationary data streams A Shaker, E Hüllermeier Proceedings of the 8th International Conference on Computer Recognition …, 2013 | 8 | 2013 |
| MILIE: Modular & Iterative Multilingual Open Information Extraction B Kotnis, K Gashteovski, D Rubio, A Shaker, V Rodriguez-Tembras, ... Proceedings of the 60th Annual Meeting of the Association for Computational …, 2022 | 6 | 2022 |
| Towards interpretable multi-task learning using bilevel programming F Alesiani, S Yu, A Shaker, W Yin Machine Learning and Knowledge Discovery in Databases: European Conference …, 2021 | 3 | 2021 |
| Online meta-forest for regression data streams A Shaker, C Gärtner, X He, S Yu 2020 International Joint Conference on Neural Networks (IJCNN), 1-8, 2020 | 3 | 2020 |
| Learning TSK fuzzy rules from data streams A Shaker, W Heldt, E Hüllermeier Machine Learning and Knowledge Discovery in Databases: European Conference …, 2017 | 3 | 2017 |
| Method and system for adaptive online meta learning from data streams A Shaker, C Gaertner, X He US Patent 11,521,132, 2022 | 2 | 2022 |
Eyke HüllermeierProfessor of Computer Science, Paderborn UniversityGeverifieerd e-mailadres voor upb.de
