Ammar Shaker
Ammar Shaker
NEC Laboratories Europe GmbH
Verified email at neclab.eu
Title
Cited by
Cited by
Year
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
2572014
On-line elimination of local redundancies in evolving fuzzy systems
E Lughofer, JL Bouchot, A Shaker
Evolving systems 2 (3), 165-187, 2011
1002011
IBLStreams: a system for instance-based classification and regression on data streams
A Shaker, E Hüllermeier
Evolving Systems 3 (4), 235-249, 2012
802012
Self-adaptive and local strategies for a smooth treatment of drifts in data streams
A Shaker, E Lughofer
Evolving Systems 5 (4), 239-257, 2014
592014
Evolving fuzzy pattern trees for binary classification on data streams
A Shaker, R Senge, E Hüllermeier
Information Sciences 220, 34-45, 2013
362013
SciPlore Xtract: extracting titles from scientific PDF documents by analyzing style information (Font Size)
J Beel, B Gipp, A Shaker, N Friedrich
International Conference on Theory and Practice of Digital Libraries, 413-416, 2010
302010
Recovery analysis for adaptive learning from non-stationary data streams: Experimental design and case study
A Shaker, E Hüllermeier
Neurocomputing 150, 250-264, 2015
282015
Z? liobaite, I
G Krempl
BrzeziÁski, D., Hüllermeier, E., Last, M., Lemaire, V., Noack, T., Shaker, A …, 2014
202014
Instance-based classification and regression on data streams
A Shaker, E Hüllermeier
Learning in Non-Stationary Environments, 185-201, 2012
172012
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
102016
Metabags: Bagged meta-decision trees for regression
J Khiari, L Moreira-Matias, A Shaker, B Ženko, S Džeroski
Joint european conference on machine learning and knowledge discovery in …, 2018
92018
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
82013
Recovery analysis for adaptive learning from non-stationary data streams
A Shaker, E Hüllermeier
Proceedings of the 8th International Conference on Computer Recognition …, 2013
72013
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
62014
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
52019
Learning TSK fuzzy rules from data streams
A Shaker, W Heldt, E Hüllermeier
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2017
22017
Towards Interpretable Multi-Task Learning Using Bilevel Programming
F Alesiani, S Yu, A Shaker, W Yin
arXiv preprint arXiv:2009.05483, 2020
12020
Measuring the Discrepancy between Conditional Distributions: Methods, Properties and Applications
S Yu, A Shaker, F Alesiani, JC Principe
arXiv preprint arXiv:2005.02196, 2020
12020
Hazard analysis on data streams
A Shaker, E Hüllermeier
Proceedings. 22. Workshop Computational Intelligence, Dortmund, 6.-7 …, 2014
12014
Event history analysis on data streams: An application to earthquake occurrence
A Shaker, E Hüllermeier
Proceedings of RealStream, 43-46, 2013
12013
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