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

2018

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

2017

Przemysław Spurek General Split Gaussian Cross-Entropy Clustering, EXPERT SYST APPL vol. 68 (2017), 58–68
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
Ociepka Michał, Przemysław Rola, Przemysław Spurek, Jacek Tabor ICA based on asymmetry, PATTERN RECOGN vol. 67 (2017), 230-244
Krzysztof Byrski, Przemysław Spurek, Jacek Tabor Active Function Cross-Entropy Clustering, EXPERT SYST APPL vol. 72 (2017), 49–66
Andrzej Bojarski, Wojciech Czarnecki, Stanisław Jastrzębski, Damian Leśniak, Sabina Podlewska Quo vadis G Protein-Coupled Receptor ligands? A tool for analysis of the emergence of new groups of compounds over time, BIOORG MED CHEM LETT vol. 27 (2017), 626-631
Devansh Arpit, Nicolas Ballas, Aaron Courville, Bengio Emmanuel, Asja Fischer, Stanisław Jastrzębski, Maxinder S. Kanwal, David Krueger, Tegan Maharaj Deep Nets Don't Learn via Memorization, INTERNATIONAL CONFERENCE ON LEARNING REPRESENTATIONS (WORKSHOP TRACK) (2017),
Devansh Arpit, Nicolas Ballas, Yoshua Bengio, Bengio Emmanuel, Asja Fischer, Stanisław Jastrzębski, Maxinder S. Kanwal, David Krueger, Simon Lacoste-Julien, Tegan Maharaj A Closer Look at Memorization in Deep Networks, (2017),
Konrad Kamieniecki, Krzysztof Misztal, Przemysław Spurek, Marek Śmieja, Jacek Tabor R Package CEC , NEUROCOMPUTING vol. 237 (2017), 410–413
Yoshua Bengio, Bahdanau Dzmitry, Grefenstette Edward, Stanisław Jastrzębski, Vincent Pascal, Bosc Tom Learning to Compute Word Embeddings On the Fly, ARXIV (2017),
Wojciech Czarnecki, Stanisław Jastrzębski, Damian Leśniak How to evaluate word embeddings? On importance of data efficiency and simple supervised tasks, ARXIV (2017),
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
Maciej Brzeski, Przemysław Spurek Uniform Cross-entropy Clustering, SCHEDAE INFORMATICAE vol. 25 (2017), 117-126
Devansh Arpit, Nicolas Ballas, Yoshua Bengio, Stanisław Jastrzębski Residual connections encourage iterative inference, ARXIV (2017),

2016

Wojciech Czarnecki, Stanisław Jastrzębski, Damian Leśniak Learning to SMILE(S), INTERNATIONAL CONFERENCE ON LEARNING REPRESENTATIONS (WORKSHOP TRACK) (2016),
Stanisław Jastrzębski, Igor Sieradzki On Certain Limitations of Recursive Representation Model, SCHEDAE INFORMATICAE vol. 25 (2016), 37-47
Wiesław Pałka, Przemysław Spurek Clustering of Gaussian distributions, 2016 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN) vol. IEEE (2016), 3346--3353
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
Przemysław Spurek, Jacek Tabor Maximum Likelihood Estimation and Optimal Coordinates, INTERNATIONAL CONFERENCE ON SYSTEMS SCIENCE, 2016 vol. Springer (2016), 3-13

2015

Wojciech Czarnecki, Stanisław Jastrzębski, Sabina Podlewska, Igor Sieradzki Active Learning of Compounds Activity - Towards Scientifically Sound Simulation of Drug Candidates Identification, PROCEEDINGS OF 2ND WORKSHOP ON MACHINE LEARNING IN LIFE SCIENCES (2015), 40-51
Wojciech Czarnecki, Stanisław Jastrzębski Analysis of compounds activity concept learned by SVM using robust Jaccard based low-dimensional embedding, SCHEDAE INFORMATICAE vol. 24 (2015), 9-19
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)
Przemysław Spurek, Łukasz Struski, Jacek Tabor Subspace memory clustering, SCHEDAE INFORMATICAE vol. 24 (2015), 133-142
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
Mateusz Malik, Przemysław Spurek, Jacek Tabor Cross-Entropy based image thresholding, SCHEDAE INFORMATICAE vol. 24 (2015), 21-29
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
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
Wojciech Czarnecki, Igor Podolak Adaptive Active Learning as a Multi-armed Bandit Problem, FRONTIERS IN ARTIFICIAL INTELLIGENCE AND APPLICATIONS vol. 263 (2014), 989-990
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

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
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
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
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
IT Podolak, A Roman, Theoretical foundations and experimental results for a hierarchical classifier with overlapping clusters, Computational Intelligence 29 (2), 357-388 (2013)
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

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
IT Podolak, Hierarchiczny klasyfikator z nakładającymi się grupami klas, Wydawnictwo Uniwersytetu Jagiellońskiego WUJ (2012)
Przemysław Spurek, Jacek Tabor Numerical verification of condition for approximately midconvex functions, AEQUATIONES MATH vol. 83 (2012), 223-237

2011

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
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
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 Bartocha, IT Podolak, Classifier Ensembles for Virtual Concept Drift–The DEnBoost Algorithm, International Conference on Hybrid Artificial Intelligence Systems, 164-171 (2011)
K Misztal, P Spurek, J Tabor, k-means Approach to the Karhunen-Love Transform, arXiv preprint arXiv:1109.3994 (2011)

2009

Kamil Bartocha, Igor Podolak Hierarchical Classifier with Growing Neural Gas clustering, LECTURE NOTES IN COMPUTER SCIENCE vol. 5495 (2009), 283-292
IT Podolak, K Bartocha, A Hierarchical Classifier with Growing Neural Gas Clustering., ICANNGA, 283-292 (2009)
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

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