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 Łukasz Struski dr Wojciech M. Czarnecki
mgr Stanisław Jastrzębski mgr Damian Leśniak mgr Maciej J. Mikulski mgr Agnieszka Pocha mgr Igor Sieradzki mgr Magdalena Wiercioch mgr Konrad Żołna mgr Jakub Chłędowski mgr Piotr Kowenzowski mgr Łukasz Maziarka

2018

Krzysztof Byrski, Przemysław Spurek, Jacek Tabor Online updating of active function cross-entropy clustering, PATTERN ANAL APPL (2018),
Przemysław Spurek, Łukasz Struski, Jacek Tabor Lossy Compression Approach to Subspace Clustering, INFORM SCIENCES vol. 435 (2018), 161-183
Igor Podolak, Adam Roman, Marek Szykuła, Bartosz Zieliński A machine learning approach to synchronization of automata, EXPERT SYST APPL (2018), 357-371
J Tabor, S Knop, P Spurek, I Podolak, M Mazur, S Jastrzębski, Cramer-Wold AutoEncoder, arXiv preprint arXiv:1805.09235 (2018)
D Leśniak, I Sieradzki, I Podolak, On Latent Distributions Without Finite Mean in Generative Models, arXiv preprint arXiv:1806.01670 (2018)
P Spurek, J Tabor, M Śmieja, Fast independent component analysis algorithm with a simple closed-form solution, Knowledge-Based Systems (2018)
P Spurek, P Rola, J Tabor, A Czechowski, ICA based on Split Generalized Gaussian, arXiv preprint arXiv:1802.05550 (2018)
M Smieja, Ł Struski, J Tabor, B Zieliński, P Spurek, Processing of missing data by neural networks, arXiv preprint arXiv:1805.07405 (2018)

2017

Krzysztof Byrski, Przemysław Spurek, Jacek Tabor Active Function Cross-Entropy Clustering, EXPERT SYST APPL vol. 72 (2017), 49–66
Ociepka Michał, Przemysław Rola, Przemysław Spurek, Jacek Tabor ICA based on asymmetry, PATTERN RECOGN vol. 67 (2017), 230-244
Monika Brzychczy-Włoch, Krzysztof Misztal, Dorota Ochońska, Anna Plichta, Przemysław Spurek, Bartosz Zieliński Deep learning approach to bacterial colony classification, PLOS ONE vol. 12 (9) (2017), 1-14
Przemysław Spurek, Marek Śmieja, Jacek Tabor SVM with a neutral class, PATTERN ANAL APPL (2017), 17
Przemysław Spurek General Split Gaussian Cross-Entropy Clustering, EXPERT SYST APPL vol. 68 (2017), 58–68
Maciej Brzeski, Przemysław Spurek Uniform Cross-entropy Clustering, SCHEDAE INFORMATICAE vol. 25 (2017), 117-126
Krzysztof Hajto, Konrad Kamieniecki, Krzysztof Misztal, Przemysław Spurek Split-and-merge Tweak in Cross Entropy Clustering, COMPUTER INFORMATION SYSTEMS AND INDUSTRIAL MANAGEMENT: 16TH IFIP TC8 INTERNATIONAL CONFERENCE (2017), 193 - 204
Magdalena Wiercioch Towards Learning Word Representation, SCHEDAE INFORMATICAE vol. 25 (2017), 103–115
Marek Śmieja, Magdalena Wiercioch Constrained clustering with a complex cluster structure, ADV DATA ANAL CLASSI vol. 11/3 (2017), 493-518
Konrad Kamieniecki, Krzysztof Misztal, Przemysław Spurek, Marek Śmieja, Jacek Tabor R Package CEC , NEUROCOMPUTING vol. 237 (2017), 410–413
Magdalena Wiercioch Feature Selection in Texts, PROCEEDINGS OF THE 10TH INTERNATIONAL CONFERENCE ON COMPUTER RECOGNITION SYSTEMS CORES 2017 vol. 578. Advances in Intelligent Systems and Computing (2017), 336-345

2016

Wiesław Pałka, Przemysław Spurek Clustering of Gaussian distributions, 2016 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN) vol. IEEE (2016), 3346--3353
Przemysław Spurek, Jacek Tabor Maximum Likelihood Estimation and Optimal Coordinates, INTERNATIONAL CONFERENCE ON SYSTEMS SCIENCE, 2016 vol. Springer (2016), 3-13
Krzysztof Misztal, Michał Podgórski, Przemysław Spurek, Jacek Tabor, Arkadiusz Tomczyk Detection of Elongated Structures with Hierarchical Active Partitions and CEC-Based Image Representation, LECTURE NOTES IN COMPUTER SCIENCE vol. 403 (2016), 159-168

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)
Marek Śmieja, Magdalena Wiercioch Mixture of metrics optimization for machine learning problems, SCHEDAE INFORMATICAE vol. 24 (2015), 133-142
Mateusz Malik, Przemysław Spurek, Jacek Tabor Cross-Entropy based image thresholding, SCHEDAE INFORMATICAE vol. 24 (2015), 21-29
Krzysztof Misztal, Emil Saeed, Khalid Saeed, Przemysław Spurek, Jacek Tabor Cross entropy clustering approach to iris segmentation for biometrics purpose, SCHEDAE INFORMATICAE vol. 24 (2015), 31-40
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
Przemysław Spurek, Łukasz Struski, Jacek Tabor Subspace memory clustering, SCHEDAE INFORMATICAE vol. 24 (2015), 133-142
Przemysław Spurek, Jacek Tabor, Mateusz Wójcik Cross-Entropy Clustering Approach to One-Class Classification, LECTURE NOTES IN COMPUTER SCIENCE vol. 9119 (2015), 481-490

2014

Przemysław Spurek, Jacek Tabor Cross Entropy Clustering, PATTERN RECOGN vol. 47 (2014), 3046–3059
Krzysztof Misztal, Przemysław Spurek, Marek Śmieja Subspaces Clustering Approach to Lossy Image Compression, LECTURE NOTES IN COMPUTER SCIENCE vol. 8838 (2014), 571-579
Przemysław Spurek, Elżbieta Zając Metody analizy mikroskopowych obrazów warstw C-Pd, (2014), "Świat nanotechnologii. Warstwy nanokompozytowe węglowo-palladowe. Badania i technologia", Wydawnictwa Uniwersytetu Warszawskiego
Wojciech Czarnecki, Igor Podolak Adaptive Active Learning as a Multi-armed Bandit Problem, FRONTIERS IN ARTIFICIAL INTELLIGENCE AND APPLICATIONS vol. 263 (2014), 989-990
Alena Chaikouskaya, Przemysław Spurek, Jacek Tabor, Elżbieta Zając A local Gaussian filter and adaptive morphology as tools for completing partially discontinuous curves, COMPUTER INFORMATION SYSTEMS AND INDUSTRIAL MANAGEMENT vol. 8838 (2014), 559-570

2013

Przemysław Spurek, Jacek Tabor The memory center, INFORM SCIENCES vol. 252 (2013), 132–143
Igor Podolak, Adam Roman Theoretical foundations and practical results for a hierarchical classifier with overlapping clusters, COMPUT INTELL-US (2013), 357-388
Przemysław Spurek, Jacek Tabor, Elżbieta Zając Detection of Disk-Like Particles in Electron Microscopy Images, ADVANCES IN INTELLIGENT SYSTEMS AND COMPUTING vol. 226 (2013), 411-417
Stanisław Jastrzębski, Igor Podolak Density Invariant Detection of Osteoporosis Using Growing Neural Gas, PROCEEDINGS OF THE 8TH INTERNATIONAL CONFERENCE ON COMPUTER RECOGNITION SYSTEMS CORES 2013 vol. Springer International Publishing (2013), 629-638
P Spurek, J Tabor, Optimal Rescaling and the Mahalanobis Distance, arXiv preprint arXiv:1306.2004 (2013)
Wojciech Czarnecki, Igor Podolak Machine Learning with Known Input Data Uncertainty Measure, LECTURE NOTES IN COMPUTER SCIENCE (2013), 379-388
IT Podolak, A Roman, Theoretical foundations and experimental results for a hierarchical classifier with overlapping clusters, Computational Intelligence 29 (2), 357-388 (2013)
Krzysztof Misztal, Przemysław Spurek, Jacek Tabor Weighted Approach to Projective Clustering, COMPUTER INFORMATION SYSTEMS AND INDUSTRIAL MANAGEMENT LECTURE NOTES IN COMPUTER SCIENCE vol. 8104 (2013), 367-378

2012

Dariusz Jędrzejczyk, Igor Podolak, Adam Roman Application of Hierarchical Classifier to Minimal Synchronizing Word problem, LECTURE NOTES IN COMPUTER SCIENCE vol. 7267 (2012), 421-429
Przemysław Spurek, Jacek Tabor Numerical verification of condition for approximately midconvex functions, AEQUATIONES MATH vol. 83 (2012), 223-237
IT Podolak, Hierarchiczny klasyfikator z nakładającymi się grupami klas, Wydawnictwo Uniwersytetu Jagiellońskiego WUJ (2012)

2011

Stanisław Brodowski, Igor Podolak Hierarchical Estimator, EXPERT SYST APPL vol. 38 (2011), 12237–12248
IT Podolak, A Roman, CORES: fusion of supervised and unsupervised training methods for a multi-class classification problem, Pattern Analysis and Applications 14 (4), 395-413 (2011)
Igor Podolak, Adam Roman Risk function estimation for subproblems in a hierarchical classifier, PATTERN RECOGN LETT vol. 32(15) (2011), 2136-2142
Igor Podolak, Adam Roman Fusion of supervised and unsupervised training methods for a multi-class classification problem, PATTERN ANAL APPL vol. 14(4) (2011), 395-413
K Bartocha, IT Podolak, Classifier Ensembles for Virtual Concept Drift–The DEnBoost Algorithm, International Conference on Hybrid Artificial Intelligence Systems, 164-171 (2011)
Agnieszka Mielniczek (Deszyńska), Igor Podolak, Adam Roman On the number of clusterings in a hierarchical classification model with overlapping clusters, SCHEDAE INFORMATICAE vol. 20 (2011), 137-157
Igor Podolak, Adam Roman Risk estimation for hierarchical classifier, LECTURE NOTES IN ARTIFICIAL INTELLIGENCE vol. 6678 (2011), 156-163
K Misztal, P Spurek, J Tabor, k-means Approach to the Karhunen-Love Transform, arXiv preprint arXiv:1109.3994 (2011)

2009

IT Podolak, K Bartocha, A hierarchical classifier with growing neural gas clustering, International Conference on Adaptive and Natural Computing Algorithms, 283-292 (2009)
Kamil Bartocha, Igor Podolak Hierarchical Classifier with Growing Neural Gas clustering, LECTURE NOTES IN COMPUTER SCIENCE vol. 5495 (2009), 283-292
Igor Podolak, Adam Roman A new notion of weakness in classification theory vol. 57 (2009), "Advances in Intelligent and Soft Computing", Springer Verlag (połaczony z Kluwer Academic Publishing)

2008

Igor Podolak Hierarchical classifier with overlapping class groups, EXPERT SYST APPL vol. 1 (2008), 673-682
Bartosz Bierkowski, Piotr Kalita, Igor Podolak, Adam Roman Algorithm for intelligent prediction of requests in business systems, LECTURE NOTES IN COMPUTER SCIENCE vol. 4910 (2008), 696-707

2007

IT Podolak, Hierarchical rules for a hierarchical classifier, International Conference on Adaptive and Natural Computing Algorithms, 749-757 (2007)

2005

H Telega, I Podolak, Hill Crunching Clustered Genetic Search and its Improvements, Wyższa Szkoła Biznesu–National-Louis University (2005)

2004

I Podolak, U Demšar, Discovering structure in geographical metadata, Proceedings of the 12th conference in Geoinformatics, 1-7 (2004)
A Bielecki, IT Podolak, M Bielecka, Neuronal algorithm of nonlinear regression, Schedae Informaticae 13 (2004)

2003

IT Podolak, A Bielecki, A neural system of phonematic transformation, Task Quarterly 7 (1), 115-130 (2003)
BA Podolak I.T., A neuronal system for phonematic transformation, TASK Quaterly 7 (1), 115-130 (2003)

2002

D Xi, IT Podolak, SW Lee, Facial component extraction and face recognition with support vector machines, Automatic Face and Gesture Recognition, 2002. Proceedings. Fifth IEEE… (2002)

2001

A Bielecki, M Bielecka, IT Podolak, Symulacja pewnego nieliniowego modelu ekonometrycznego przy pomocy sieci neuronowych, Przegląd Statystyczny 48 (1-2), 151-159 (2001)

2000

LSW Podolak I.T., Finding input symbol representations for neural networks, 7th Int. Conf. on Neural Informations Processing, 1174-1179 (2000)
IT Podolak, SW Lee, A Bielecki, E Majkut, A hybrid neural system for phonematic transformation, Pattern Recognition, 2000. Proceedings. 15th International Conference on 2… (2000)

1999

IT Podolak, Feedforward neural network's sensitivity to input data representation, Computer physics communications 117 (1-2), 181-188 (1999)

1998

IT Podolak, Functional graph model of a neural network, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 28… (1998)

1996

A Bielecki, IT Podolak, J Wosiek, E Majkut, Phonematic translation of polish texts by the neural network, ACTA PHYSICA POLONICA SERIES B 27, 2253-2264 (1996)

Contact Us

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