prof. dr hab. Jacek Tabor dr hab. Igor T. Podolak dr Jarek Duda dr Krzysztof Misztal dr hab. Adam Roman dr Marek Śmieja dr Przemysław Spurek dr Marcin Żelawski dr Bartosz Zieliński dr Wojciech M. Czarnecki
mgr Stanisław Jastrzębski mgr Damian Leśniak mgr Maciej Mikulski mgr Agnieszka Pocha mgr Igor Sieradzki mgr Magdalena Wiercioch mgr Konrad Żołna mgr Jakub Chłędowski mgr Piotr Kowenzowski mgr Łukasz Maziarka

Main collaborators

prof. dr hab. Jacek Tabor
18
dr Przemysław Spurek
4
mgr Magdalena Wiercioch
3
dr Krzysztof Misztal
3
dr Bartosz Zieliński
1
dr Marek Śmieja
Assistant professor http://ww2.ii.uj.edu.pl/~smieja/ marek.smieja@uj.edu.pl
clustering methods, entropy theory, semi-supervised learning
room 2163
office hours
Thursday, 14:00-16:00

Papers

2018

Przemysław Spurek, Marek Śmieja, Jacek Tabor SVM with a neutral class, PATTERN ANAL APPL (2018), 17

2017

Łukasz Struski, Marek Śmieja, Jacek Tabor Semi-supervised model-based clustering with controlled clusters leakage, EXPERT SYST APPL vol. 85 (2017), 146-157
Bernhard C. Geiger, Marek Śmieja Semi-supervised cross-entropy clustering with information bottleneck constraint, INFORM SCIENCES vol. 421 (2017), 245-271
Ł Struski, M Śmieja, J Tabor, Pointed subspace approach to incomplete data, arXiv preprint arXiv:1705.00840 (2017)
M Śmieja, K Hajto, J Tabor, Efficient mixture model for clustering of sparse high dimensional binary data, arXiv preprint arXiv:1707.03157 (2017)
Konrad Kamieniecki, Krzysztof Misztal, Przemysław Spurek, Marek Śmieja, Jacek Tabor R Package CEC , NEUROCOMPUTING vol. 237 (2017), 410–413
Marek Śmieja, Magdalena Wiercioch Constrained clustering with a complex cluster structure, ADV DATA ANAL CLASSI vol. 11/3 (2017), 493-518
Rafał Kafel, Marek Śmieja, Dawid Warszycki Practical application of the Average Information Content Maximization (AIC-MAX) algorithm – selection of the most important structural features for serotonin receptor ligands, MOL DIVERS vol. 21/2 (2017), 407-412
Łukasz Struski, Marek Śmieja, Jacek Tabor, Bartosz Zieliński Regression SVM for incomplete data, SCHEDAE INFORMATICAE (2017),

2016

U Fechner, C de Graaf, AE Torda, S Góssregen, A Evers, H Matter, ..., 11th German Conference on Chemoinformatics (GCC 2015), Journal of Cheminformatics 8 (1), 18 (2016)
Marek Śmieja, Dawid Warszycki Average Information Content Maximization - a new approach for fingerprint hybridization and reduction, PLOS ONE vol. 11/1 (2016), e0146666
Szymon Nakoneczny, Marek Śmieja Natural language processing methods in biological activity prediction, PROCEEDINGS OF ECML PKDD WORKSHOP ON MACHINE LEARNING IN LIFE SCIENCES (2016), 25-36
Szymon Nakoneczny, Marek Śmieja, Jacek Tabor Fast entropy clustering of sparse high dimensional binary data, PROCEEDNIGS OF IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN 2016) (2016), 2397-2404
Ł Struski, M Śmieja, J Tabor, Incomplete data representation for SVM classification, arXiv preprint arXiv:1612.01480 (2016)

2015

Marek Śmieja, Jacek Tabor Entropy approximation in lossy source coding problem, ENTROPY-SWITZ vol. 17/5 (2015), 3400-3418
Marek Śmieja Weighted approach to general entropy function, IMA J MATH CONTROL I vol. 32/2 (2015), 329-327
Marek Śmieja Mixture of metrics optimization for machine learning problems, SCHEDAE INFORMATICAE vol. 24 (2015), 133-142
Marek Śmieja, Jacek Tabor Spherical Wards clustering and generalized Voronoi diagrams, PROCEEDING OF IEEE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND ADVANCED ANALYTICS vol. 36678 (2015), 10
Marek Śmieja, Jacek Tabor, Magdalena Wiercioch Probability Index of Metric Correspondence as a measure of visualization reliability, PROCEEDINGS OF ECML PKDD WORKSHOP ON MACHINE LEARNING IN LIFE SCIENCES (2015), 16-27
Marek Śmieja, Magdalena Wiercioch Mixture of metrics optimization for machine learning problems, SCHEDAE INFORMATICAE (2015),
J Tabor, P Spurek, K Kamieniecki, M Śmieja, K Misztal, Introduction to Cross-Entropy Clustering The R Package CEC, arXiv preprint arXiv:1508.04559 (2015)

2014

Andrzej Bojarski, Marek Śmieja, Jacek Tabor, Dawid Warszycki Asymmetric Clustering Index in a case study of 5-HT1A receptor ligands, PLOS ONE vol. 9(7) (2014), e102069
Krzysztof Misztal, Przemysław Spurek, Marek Śmieja Subspaces Clustering Approach to Lossy Image Compression, LECTURE NOTES IN COMPUTER SCIENCE vol. 8838 (2014), 571-579
Marek Śmieja, Jacek Tabor Renyi entropy dimension of the mixture of measures, PROCEEDINGS OF SCIENCE AND INFORMATION CONFERENCE (2014), 685-689
M Smieja, J Tabor, Rnyi entropy dimension of the mixture of measures, Science and Information Conference (SAI), 2014 (2014)

2013

Marek Śmieja, Jacek Tabor Image segmentation with use of cross-entropy clustering, ADVANCES IN INTELLIGENT SYSTEMS AND COMPUTING vol. 226 (2013), 403-409

2012

Marek Śmieja, Jacek Tabor Entropy of the mixture of source and entropy dimension, IEEE T INFORM THEORY vol. 58(5) (2012), 2719-2728

2011

M Smieja, J Tabor, Entropy of the Mixture of Sources and Entropy Dimension, Information Theory, IEEE Transactions on, 1-1 (2011)

Contact Us

Igor Podolak, PhD
Group of Machine Learning Research
Faculty of Mathematics and Computer Science
ul. Lojasiewicza 6
30-342, Cracow, Poland