Bogdan Gabrys

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Katarzyna MusialProfessor in Network Science, University of Technology Sydney, AustraliaVerified email at uts.edu.au
Marcin BudkaData Scientist, Bournemouth UniversityVerified email at bournemouth.ac.uk
Christiane LemkeeBay Classifieds GermanyVerified email at unister-gmbh.de
Khuat Thanh TungData Science Institute - University of Technology SydneyVerified email at uts.edu.au
Andrzej BargielaProfessor of Computer Science and CEO InfoHub LtdVerified email at nottingham.ac.uk
David Jacob KedzioraVerified email at uts.edu.au
Indrė ŽliobaitėProfessor, University of HelsinkiVerified email at helsinki.fi
Manuel Martín SalvadorAI Engineer, Blink TechnologiesVerified email at blinkeye.ai
Joakim SkardingPhD candidate, University of Technology SydneyVerified email at uts.edu.au
Xuanyi DongAugment <- Google DeepmindVerified email at augmentcode.com
Damien FayHead of research, HPE labs IrelandVerified email at hpe.com
Rashid BakirovBournemouth UniversityVerified email at bournemouth.ac.uk
Di JinTianjin University, ProfessorVerified email at tju.edu.cn
Neil VaughanUniversity of ExeterVerified email at exeter.ac.uk
Robert HowlettKES International ResearchVerified email at kesinternational.org
Athanasios TsakonasUniversity of the AegeanVerified email at stt.aegean.gr
Mai LeData Scientist, BT OpenreachVerified email at openreach.co.uk
Dongxiao HeTianjin University, Professor of Computer ScienceVerified email at tju.edu.cn
Abbas Raza AliMachine Learning ScientistVerified email at bournemouth.ac.uk
Mohamed Medhat GaberProfessor in Data Analytics, Birmingham City UniversityVerified email at bcu.ac.uk

Bogdan Gabrys

Prof. of Data Science, University of Technology Sydney

Verified email at uts.edu.au - Homepage

Computational Intelligence Data Science Complex Adaptive Systems Machine Learning Predictive Analytics


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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	1969	2009
Classifier selection for majority voting D Ruta, B Gabrys Information fusion 6 (1), 63-81, 2005	781	2005
Review of adaptation mechanisms for data-driven soft sensors P Kadlec, R Grbić, B Gabrys Computers & chemical engineering 35 (1), 1-24, 2011	586	2011
An overview of classifier fusion methods D Ruta, B Gabrys Computing and Information systems 7 (1), 1-10, 2000	553	2000
General fuzzy min-max neural network for clustering and classification B Gabrys, A Bargiela IEEE transactions on neural networks 11 (3), 769-783, 2000	524	2000
Metalearning: a survey of trends and technologies C Lemke, M Budka, B Gabrys Artificial intelligence review 44, 117-130, 2015	497	2015
Meta-learning for time series forecasting and forecast combination C Lemke, B Gabrys Neurocomputing 73 (10-12), 2006-2016, 2010	311	2010
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	303	2021
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	198	2016
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	196	2021
Local learning‐based adaptive soft sensor for catalyst activation prediction P Kadlec, B Gabrys AIChE Journal 57 (5), 1288-1301, 2011	190	2011
An overview of self-adaptive technologies within virtual reality training N Vaughan, B Gabrys, VN Dubey Computer Science Review 22, 65-87, 2016	176	2016
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	148	2020
Genetic algorithms in classifier fusion B Gabrys, D Ruta Applied soft computing 6 (4), 337-347, 2006	147	2006
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	120	2012
Adaptive community detection incorporating topology and content in social networks M Qin, D Jin, D He, B Gabrys, K Musial Proceedings of the 2017 IEEE/ACM International Conference on Advances in …, 2017	111	2017
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	107	2002
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	101	2001
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	93	2002
Adaptive preprocessing for streaming data I Zliobaite, B Gabrys IEEE transactions on knowledge and data Engineering 26 (2), 309-321, 2012	90	2012

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