Niklas Lavesson

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Håkan GrahnProfessor of Computer Engineering, Blekinge Institute of Technology, SwedenVerified email at bth.se
Paul DavidssonProfessor of Computer Science, Malmö University, SwedenVerified email at mau.se
Veselka BoevaProfessor of Computer Science, Blekinge Institute of TechnologyVerified email at bth.se
Eva García-MartínPhD in Machine Learning. Data Scientist at Ekkono SolutionsVerified email at ekkono.ai
Raja Khurram ShahzadVerified email at khurram.com.pk
Martin BoldtAssociate professor, Blekinge Institute of Technology, SwedenVerified email at bth.se
Shahrooz AbghariPhD in Computer Science, Blekinge Institute of TechnologyVerified email at bth.se
Florian WestphalAssistant Professor, Jönköping UniversityVerified email at ju.se
Anton BorgBlekinge Institute of TechnologyVerified email at bth.se
Andreas JacobssonAssociate Professor in Computer Science @ Malmö UniversityVerified email at mah.se
Marie PerssonLecturer in Computer Science, Blekinge Institute of TechnologyVerified email at bth.se
Shyhtsun Felix WuUniversity of California, DavisVerified email at cs.ucdavis.edu
Hiva AlahyariChalmers/Göteborg UniversityVerified email at chalmers.se
Dirk VanhoudtVITOVerified email at vito.be
Marco BertoniProfessor, Product Development Research Lab, Blekinge Institute of TechnologyVerified email at bth.se
Ola IsakssonFull Professor in Product Development, ChalmersVerified email at chalmers.se
Sophie I.HallstedtProfessor, Blekinge Institute of Technology, SwedenVerified email at bth.se
Emiliano CasalicchioSapienza University of Rome - Computer Science Dep.Verified email at uniroma1.it
Jeff RoweUC DavisVerified email at ucdavis.edu
Maria RiveiroAssociate Professor of Computer Science, Jönköping UniversityVerified email at ju.se

Niklas Lavesson

Professor of Computer Science, School of Engineering, Jönköping University

Verified email at ju.se - Homepage

Machine Learning Data Mining Data Science Artificial Intelligence


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User-oriented assessment of classification model understandability H Allahyari, N Lavesson 11th Scandinavian Conference on Artificial intelligence, 11-19, 2011	65	2011
Quantifying the impact of learning algorithm parameter tuning N Lavesson, P Davidsson AAAI 6, 395-400, 2006	62	2006
Open data for anomaly detection in maritime surveillance S Kazemi, S Abghari, N Lavesson, H Johnson, P Ryman Expert Systems with Applications 40 (14), 5719-5729, 2013	54	2013
CudaRF: a CUDA-based implementation of random forests H Grahn, N Lavesson, MH Lapajne, D Slat 2011 9th IEEE/ACS International Conference on Computer Systems and …, 2011	53	2011
Learning to detect spyware using end user license agreements N Lavesson, M Boldt, P Davidsson, A Jacobsson Knowledge and Information Systems 26 (2), 285-307, 2011	47	2011
Detecting serial residential burglaries using clustering A Borg, M Boldt, N Lavesson, U Melander, V Boeva Expert Systems with Applications 41 (11), 5252-5266, 2014	40	2014
Operational Demand Forecasting in District Heating Systems using Ensembles of Online Machine Learning Algorithms C Johansson, M Bergkvist, D Geysen, N Lavesson, D Vanhoudt International Symposium on District Heating and Cooling, 2016	35	2016
Detection of spyware by mining executable files RK Shahzad, SI Haider, N Lavesson 2010 International Conference on Availability, Reliability and Security, 295-302, 2010	35	2010
Model based decision support for value and sustainability in product development O Isaksson, M Bertoni, S Hallstedt, N Lavesson 20th International Conference on Engineering Design (ICED), Milan, 2015	30	2015
Comparative analysis of voting schemes for ensemble-based malware detection RK Shahzad, N Lavesson Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable …, 2013	30	2013
Document image binarization using recurrent neural networks F Westphal, N Lavesson, H Grahn 2018 13th IAPR International Workshop on Document Analysis Systems (DAS …, 2018	29	2018
Evaluating learning algorithms and classifiers N Lavesson, P Davidsson International Journal of Intelligent Information and Database Systems 1 (1 …, 2007	27	2007
Accurate adware detection using opcode sequence extraction RK Shahzad, N Lavesson, H Johnson 2011 Sixth International Conference on Availability, Reliability and …, 2011	26	2011
Veto-based malware detection RK Shahzad, N Lavesson 2012 Seventh International Conference on Availability, Reliability and …, 2012	24	2012
Detecting Scareware by Mining Variable Length Instruction Sequences RK Shahzad, N Lavesson Tenth Annual Information Security South Africa Conference, 2011	24	2011
Evaluation and analysis of supervised learning algorithms and classifiers N Lavesson Blekinge Institute of Technology, 2006	21	2006
Learning machine learning: a case study N Lavesson IEEE Transactions on Education 53 (4), 672-676, 2010	19	2010
Hashtags and followers: An experimental study of the online social network Twitter E García Martín, N Lavesson, M Doroud Social Network Analysis and Mining 6 (12), 2016	18	2016
On the concept of trust in online social networks H Johnson, N Lavesson, H Zhao, SF Wu Trustworthy internet, 143-157, 2011	17	2011
Generic methods for multi-criteria evaluation N Lavesson, P Davidsson Proceedings of the 2008 SIAM International Conference on Data Mining, 541-546, 2008	17	2008

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