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Prof. dr. Marko Robnik Šikonja
Full Professor
T: +386 1 479 8241
E:Send a message
Office hours: Wednesday, from 10:00 do 11:00 (room R2.06, 2nd floor, right from the elevator).
Room: R2.06 - Kabinet
Description

My research interests include artificial intelligence, machine learning, data mining, natural language processing, and network analytics. In machine learning and data mining I am interested in deep neural networks, feature evaluation, explanation of prediction models, ensemble learning, and embeddings (recent papersfree software). I am (co)author of more than 150 publications, both scientific and literary. My papers have more than 4000 citations according to Google Scholar.
I tweet as @MarkoRobnikS.

Projects
Past projects
Publications
  • Jan Kralj, Marko Robnik-Šikonja, Nada Lavrač. NetSDM: semantic data mining with network analysis.Journal of machine learning research, 2019, vol. 20, pp. 1-50 PDF
  • Anita Valmarska, Dragana Miljković, Nada Lavrač, Marko Robnik-Šikonja. Analysis of medications change in Parkinson's disease progression data. Journal of intelligent information systems, 2018, 51:301–337
  • Janez Kranjc, Roman Orač, Vid Podpečan, Nada Lavrač, Marko Robnik-Šikonja. ClowdFlows: online workflows for distributed big data mining. FGCS, 2017, vol. 68, pp. 38-58 PDF
  • Marko Bohanec, Mirjana Kljajić Borštnar, Marko Robnik-Šikonja. Explaining machine learning models in sales predictions. Expert systems with applications, 2017, vol. 71, pp. 416-428 PDF
  • Anita Valmarska, Nada Lavrač, Johannes Fürnkranz, Marko Robnik-Šikonja: Refinement and selection heuristics in subgroup discovery and classification rule learning. Expert systems with applications, 81:147-162, 2017 PDF
  • Marko Robnik-Šikonja.. Data generators for learning systems based on RBF networks. IEEE transactions on neural networks and learning systems, May 2016, vol. 27, no. 5, pp. 926-938 PDF
  • Marko Robnik-Šikonja, Igor Kononenko: Explaining Classifications For Individual Instances. IEEE Transactions on Knowledge and Data Engineering, 20: 589-600, 2008 PDF
  • Marko Robnik-Šikonja, Koen Vanhoof: Evaluation of ordinal attributes at value level. Knowledge Discovery and Data Mining, 14:225-243, 2007 PDF
  • Marko Robnik-Šikonja, Igor Kononenko: Theoretical and Empirical Analysis of ReliefF and RReliefF. Machine Learning Journal, 53:23-69, 2003. PDF
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