Email: michal.wozniak@pwr.edu.pl

Unit: Faculty of Information and Communication Technology (N) » Department of Systems and Computer Networks

ul. Z. Janiszewskiego 11/17, 50-372 Wrocław
building C-3, room 114
phone +48 71 320 3539

Office hours

• Monday 11.00-13.00
• Wednesday 11.00-13.00

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Research fields

• Machine learning; data stream mining; data stream classification, concept drift; ensemble learning, classifier ensemble; inductive learning, data and web mining; learning on distributed and streaming data; pattern classification; imabalance data classification; classification with recognition with context; telemedicine and medical decision support.

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Recent papers

2017

• Koziarski M., Woźniak M., CCR: A combined cleaning and resampling algorithm for imbalanced data classification, Int. J. Appl. Math. Comput. Sci., Vol. 27, No. 4, 727-736.
• Krawczyk B., Minku L., Gama J., Stefanowski J., Woźniak M., Ensemble learning for data stream analysis: A survey, Information Fusion, Vol. 37, pp. 132-156.
• Ksieniewicz P., Grana M., Woźniak M., Paired feature multilayer ensemble - concept and evaluation of a classifier, Journal of Inteligent and Fuzzy Systems, vol. 32, issue 2, pp. 1427-1436.
• Ramirez-Gallego S., Krawczyk B., Garcia S., Benitez M.J., Wozniak M., Herrera F., Nearest Neighbor Classification for High-Speed Big Data Streams Using Spark, IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, vol. 46, issue 10, pp. 2727-2739.

2016

• Saez J.A., Krawczyk B., Woźniak M., Analyzing the oversampling of different classes and types of examples in multi-class imbalanced datasets, Pattern Recognition, vol. 57, pp. 164-178.

Papers in DONA database

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1	Proceeding paper 2023 Marcin Jasiński, Michał Woźniak, Employing convolutional neural networks for continual learning. W: Artificial Intelligence and Soft Computing : 21th International Conference, ICAISC 2022, Zakopane, June 19-23, 2022 : proceedings. Pt. 1 / eds. Leszek Rutkowski [i in.]. Cham : Springer, cop. 2023. s. 288-297. ISBN: 978-3-031-23491-0; 978-3-031-23492-7 Resources:DOIURLSFX
2	Article 2023 Paweł Ksieniewicz, Paweł Zyblewski, Weronika Borek-Marciniec, Rafał Kozik, Michał Choraś, Michał Woźniak, Alphabet Flatting as a variant of n-gram feature extraction method in ensemble classification of fake news. Engineering Applications of Artificial Intelligence. 2023, vol. 120, art. 105882, s. 1-11. ISSN: 0952-1976; 1873-6769 Resources:DOIURLSFX
3	Article 2023 Michał Panek, Adam Pomykała, Ireneusz Jabłoński, Michał Woźniak, 5G/5G+ network management employing AI-based continuous deployment. Applied Soft Computing. 2023, vol. 134, art. 109984, s. 1-13. ISSN: 1568-4946; 1872-9681 Resources:DOIURLSFX
4	Article 2023 Jędrzej Z Kozal, Michał Woźniak, Increasing depth of neural networks for life-long learning. Information Fusion. 2023, vol. 98, art. 101829, s. 1-10. ISSN: 1566-2535; 1872-6305 Resources:DOIURLSFX
5	Article 2023 Michał Woźniak, Paweł Zyblewski, Paweł Ksieniewicz, Active weighted aging ensemble for drifted data stream classification. Information Sciences. 2023, vol. 630, s. 286-304. ISSN: 0020-0255; 1872-6291 Resources:DOIURLSFX
6	Proceeding paper 2022 Jędrzej Z Kozal, Michał Leś, Paweł Zyblewski, Paweł Ksieniewicz, Michał Woźniak, Feature integration strategies for multilingual fake news classification. W: 2022 IEEE International Conference on Big Data, Dec 17 - Dec 20, 2022, Osaka, Japan : proceedings / eds. Shusaku Tsumoto [i in.]. Danvers, MA : IEEE, cop. 2022. s. 5049-5058. ISBN: 978-1-6654-8046-8; 978-1-6654-8045-1 Resources:DOIURL
7	Proceeding paper 2022 Sebastián Basterrech, Michał Woźniak, Tracking changes using Kullback-Leibler divergence for the continual learning. W: 2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC) October 9-12, 2022, Prague, Czech Republic : proceedings. Danvers, MA : IEEE, cop. 2022. s. 3279-3285. ISBN: 978-1-6654-5259-5; 978-1-6654-5258-8 Resources:DOIURL
8	Proceedings papers editing 2022 Nuno Moniz, Paula Branco, Luís Torgo, Nathalie Japkowicz, Michał Woźniak, Shuo Wang, Fourth International Workshop on Learning with Imbalanced Domains : Theory and Applications, 23 September 2022, ECML-PKDD, Grenoble, France. [Cambridge]: [JMLR], cop. 2022. 198 s. (Proceedings of Machine Learning Research, ISSN 2640-3498; vol. 183) Resources:URL
9	Proceeding paper 2022 Szymon Wojciechowski, Germán González-Almagro, Salvador García, Michał Woźniak, Adapting k-means algorithm for pair-wise constrained clustering of imbalanced data streams. W: Hybrid Artificial Intelligent Systems : 17th International Conference, HAIS 2022 Salamanca, Spain, September 5–7, 2022 : proceedings / eds. Pablo García Bringas [i in.]. Cham : Springer, cop. 2022. s. 153-163. ISBN: 978-3-031-15470-6; 978-3-031-15471-3 Resources:DOIURLSFX
10	Article 2022 Joanna A Grzyb, Michał Woźniak, SVM ensemble training for imbalanced data classification using multi-objective optimization techniques. Applied Intelligence. 2022, s. 1-18. ISSN: 0924-669X; 1573-7497 Resources:DOIURL