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Bogdan Gabrys
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Data-driven soft sensors in the process industry
P Kadlec, B Gabrys, S Strandt
Computers & chemical engineering 33 (4), 795-814, 2009
16472009
Classifier selection for majority voting
D Ruta, B Gabrys
Information fusion 6 (1), 63-81, 2005
6812005
Review of adaptation mechanisms for data-driven soft sensors
P Kadlec, R Grbić, B Gabrys
Computers & chemical engineering 35 (1), 1-24, 2011
5022011
An overview of classifier fusion methods
D Ruta, B Gabrys
Computing and Information systems 7 (1), 1-10, 2000
5012000
General fuzzy min-max neural network for clustering and classification
B Gabrys, A Bargiela
IEEE transactions on neural networks 11 (3), 769-783, 2000
4902000
Metalearning: a survey of trends and technologies
C Lemke, M Budka, B Gabrys
Artificial intelligence review 44, 117-130, 2015
4042015
Meta-learning for time series forecasting and forecast combination
C Lemke, B Gabrys
Neurocomputing 73 (10-12), 2006-2016, 2010
2592010
Local learning‐based adaptive soft sensor for catalyst activation prediction
P Kadlec, B Gabrys
AIChE Journal 57 (5), 1288-1301, 2011
1692011
The security challenges in the IoT enabled cyber-physical systems and opportunities for evolutionary computing & other computational intelligence
H He, C Maple, T Watson, A Tiwari, J Mehnen, Y Jin, B Gabrys
2016 IEEE congress on evolutionary computation (CEC), 1015-1021, 2016
1562016
Genetic algorithms in classifier fusion
B Gabrys, D Ruta
Applied soft computing 6 (4), 337-347, 2006
1372006
An overview of self-adaptive technologies within virtual reality training
N Vaughan, B Gabrys, VN Dubey
Computer Science Review 22, 65-87, 2016
1262016
Foundations and modeling of dynamic networks using dynamic graph neural networks: A survey
J Skarding, B Gabrys, K Musial
IEEE Access 9, 79143-79168, 2021
1182021
Analysis of the correlation between majority voting error and the diversity measures in multiple classifier systems
D Ruta, B Gabrys
ICSC-NAISO Academic Press, 2001
1042001
A theoretical analysis of the limits of majority voting errors for multiple classifier systems
D Ruta, B Gabrys
Pattern Analysis and Applications 5, 333-350, 2002
1012002
Next challenges for adaptive learning systems
I Zliobaite, A Bifet, M Gaber, B Gabrys, J Gama, L Minku, K Musial
ACM SIGKDD Explorations Newsletter 14 (1), 48-55, 2012
972012
Nats-bench: Benchmarking nas algorithms for architecture topology and size
X Dong, L Liu, K Musial, B Gabrys
IEEE transactions on pattern analysis and machine intelligence 44 (7), 3634-3646, 2021
952021
Neuro-fuzzy approach to processing inputs with missing values in pattern recognition problems
B Gabrys
International Journal of Approximate Reasoning 30 (3), 149-179, 2002
882002
Combining labelled and unlabelled data in the design of pattern classification systems
B Gabrys, L Petrakieva
International journal of approximate reasoning 35 (3), 251-273, 2004
802004
Multi-level graph convolutional networks for cross-platform anchor link prediction
H Chen, H Yin, X Sun, T Chen, B Gabrys, K Musial
Proceedings of the 26th ACM SIGKDD international conference on knowledge …, 2020
782020
Adaptive preprocessing for streaming data
I Zliobaite, B Gabrys
IEEE transactions on knowledge and data Engineering 26 (2), 309-321, 2012
782012
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Artikelen 1–20