Experience
    Education
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    My research has always gravitated towards pattern recognition and classification. I have dabbled in almost all aspects of the classical paradigm: feature selection, classification, clustering, data editing, etc. I have a soft spot for multiple classifier systems (classifier ensembles), specifically ensemble diversity. Publications 2015 Diez-Pastor J. F., J. J. Rodríguez, C. García-Osorio and L. I. Kuncheva, Diversity techniques improve the performance of the best imbalance learning ensembles, Information Sciences, 325, 2015, 98-117. pdf [bib] Kuncheva L.I. and M. Galar. Theoretical and empirical criteria for the edited nearest neighbour classifier, Proceedings of the 15th IEEE International Conference on Data Mining, Atlantic City, 2015, 817-822. pdf [bib] [code and data] Diez-Pastor J. F., J. J. Rodríguez, C. García-Osorio and L. I. Kuncheva, Random balance: Ensembles of variable priors classifiers for imbalanced data, Knowledge-Based Systems, 85, 2015, 96–111. (DOI http://dx.doi.org/10.1016/j.knosys.2015.04.022). pdf [bib] 2014 Christy T. and L.I. Kuncheva, Technological advancements in affective gaming: A historical survey, International Journal on Computing, 3(4), 2014, 32-41. pdf [bib] L.I. Kuncheva and A.S. Jackson, Who is missing? A new pattern recognition puzzle, S+SSPR, 2014, Joensuu, Finland, Springer, LNCS 8621 243–252. pdf [bib] W.J. Faithfull and L.I. Kuncheva, On optimum thresholding of multivariate change detectors, S+SSPR, 2014, Joensuu, Finland Springer, LNCS 8621 364–373. pdf [bib] Kuncheva L.I., D. Martinez-Rego, Kenneth S. L. Yuen, D. E. J. Linden, S. J. Johnston, A spatial discrepancy measure between voxel sets in brain imaging, Signal, Image and Video Processing, 8 (5), 2014, 913-922 (DOI: 10.1007/s11760-012-0326-0). pdf [bib] Kuncheva L. I. and J. J. Rodriguez, A weighted voting framework for classifiers ensembles, Knowledge and Information Systems 38, 2014, 259-275 (DOI: 10.1007/s10115-012-0586-6). pdf [bib] Kuncheva L.I. and W.J. Faithfull, PCA feature extraction for change detection in multidimensional unlabelled data, IEEE Transactions on Neural Networks and Learning Systems, 25(1), 2014, 69-80 (DOI: 10.1109/TNNLS.2013.2248094). pdf [bib] Marín J., D. Vázquez, A. M. López, J. Amores and L. I. Kuncheva, Occlusion handling via random subspace classifiers for human detection, IEEE Transactions on Systems, Man, and Cybernetics (Part B), 2014, 44(3), 342-354 (DOI: 10.1109/TCYB.2013.2255271) pdf [bib] Kuncheva L.I. and C.J. Whitaker, Pattern recognition and classification, Wiley StatsRef-Statistics Reference Online, 2014. pdf [bib] 2013 Kuncheva L.I., Change detection in streaming multivariate data using likelihood detectors, IEEE Transactions on Knowledge and Data Engineering, 2013, 25(5), 1175-1180 (DOI: 10.1109/TKDE.2011.226). pdf [bib] Kuncheva L.I., A bound on kappa-error diagrams for analysis of classifier ensembles, IEEE Transactions on Knowledge and Data Engineering, 2013, 25 (3), 494-501 (DOI: 10.1109/TKDE.2011.234). pdf [bib] Christy T. and L.I. Kuncheva, A.M.B.E.R. Shark Fin: An unobtrusive affective mouse, Proc ACHI2013: The 6th International Conference in Computer-Human Interactions, Nice, France, 2013 , 488-495. pdf [bib] Kuncheva L. I. and J. J. Rodriguez, Interval feature extraction for classification of event-related potentials (ERP) in EEG data analysis, Progress in Artificial Intelligence, 2(1), 2013, 65-72 (DOI: 10.1007/s13748-012-0037-3). pdf [bib]