prof. dr hab. Igor Podolak

Jednostki:

  • Wydział Matematyki i Informatyki UJ
  • Instytut Informatyki i Matematyki Komputerowej
  • Katedra Uczenia Maszynowego

Publikacje:

32.
Łukasz Struski, Michał B. Bednarczyk, Igor Podolak, Jacek Tabor
LapSum - One Method to Differentiate Them All: Ranking, Sorting and Top-k Selection, International Conference on Machine Learning [ICML], (2025),
31.
Łukasz Struski, Michał Sadowski, Tomasz Danel, Jacek Tabor, Igor Podolak
Feature-Based Interpolation and Geodesics in the Latent Spaces of Generative Models, IEEE Transactions on Neural Networks and Learning Systems vol. 35/9 (2024), 12068 - 12082
30.
Bartosz Wójcik, Marcin Przewięźlikowski, Filip Szatkowski, Maciej Wołczyk, Klaudia Bałazy, Bartłomiej Krzepkowski, Igor Podolak, Jacek Tabor, Marek Śmieja, Tomasz Trzciński
Zero time waste in pre-trained early exit neural networks, Neural Networks vol. 168 (2023), 580-601
29.
Tomasz Danel, Jan Łęski, Sabina Podlewska, Igor Podolak
Docking-based generative approaches in the search for new drug candidates, Drug Discovery Today vol. 28/2 (2023), 103439
28.
Romuald A. Janik, Igor Podolak, Łukasz Struski, Anna Ceglarek, Koryna Lewandowska, Barbara Sikora-Wachowicz, Tadeusz Marek, Magdalena Fąfrowicz
Neural spatio-temporal patterns of information processing related to cognitive conflict and correct or false recognitions, Scientific Reports vol. 12 (2022), 5271
27.
Jarosław Żygierewicz, Romuald A. Janik, Igor Podolak, Alan Drozd, Urszula Malinowska, Martyna Poziomska, Jakub Wojciechowski, Paweł Ogniewski, Paweł Niedbalski, Iwona Terczyńska, Jacek Rogala
Decoding working memory-related information from repeated psychophysiological EEG experiments using convolutional and contrastive neural networks, Journal of Neural Engineering vol. 19 (2022), 046053
26.
Szymon Knop, Przemysław Spurek, Marcin Mazur, Jacek Tabor, Igor Podolak
Batch size reconstruction-distribution trade-off in kernel based generative autoencoders, IEEE International Conference on Image Processing [ICIP], (2022), 3728-3732
25.
Romuald A. Janik, Igor Podolak, Łukasz Struski, Anna Ceglarek, Koryna Lewandowska, Barbara Sikora-Wachowicz, Tadeusz Marek, Magdalena Fafrowicz
Neural spatio-temporal patterns of information processing related to cognitive conflict and correct or false recognitions, Scientific Reports vol. 12 (5271) (2022),
24.
Szymon Knop, Marcin Mazur, Igor Podolak, Przemysław Spurek, Jacek Tabor
Generative models with kernel distance in data space, Neurocomputing vol. 487 (2022), 119-129
23.
Klaudia Bałazy, Igor Podolak, Marek Śmieja, Jacek Tabor, Tomasz Trzciński, Maciej Wołczyk, Bartosz Wójcik
Zero Time Waste: Recycling Predictions in Early Exit Neural Networks, Advances in Neural Information Processing Systems [NeurIPS](MAIN) vol. 34 (2021), 1-13
22.
Andrzej Bojarski, Rafał Kurczab, Stefan Mordalski, Igor Podolak, Agnieszka Wojtuch
2D SIFt: a matrix of ligand-receptor interactions, Journal of Cheminformatics vol. 13 (2021), Article number: 66
21.
Bartosz Bohaterewicz, Adrian Chrobak, Dominika Dudek, Magdalena Fafrowicz, Tadeusz Marek, Dagmara Mętel, Igor Podolak, Marcin Siwek, Anna Sobczak, Bartosz Wójcik
Machine learning-based identification of suicidal risk in patients with schizophrenia using multi-level resting-state fMRI features, Frontiers in Neuroscience vol. 14 (2021), 605697
20.
Tomasz Danel, Agnieszka Galanty, Igor Podolak, Irma Podolak, Michał Węgrzyn
Deep convolutional neural network for preliminary in-field classification of lichen species, Biosystems Engineering vol. 204 (2021), 15-25
19.
Stanisław Jastrzębski, Szymon Knop, Marcin Mazur, Igor Podolak, Przemysław Spurek, Jacek Tabor
Cramer-Wold Auto-Encoder, Journal of Machine Learning Research vol. 21 (2020), 1-28
18.
Arkadiusz Czekajski, Damian Leśniak, Igor Podolak, Adam Roman, Bartosz Zieliński
Variational Auto-Encoders for Generating Feature-Preserving Automata, Proceedings of Ncma 2019, Books@ocg.at (austrian Computer Society) (2019), 171-185
17.
Damian Leśniak, Igor Podolak, Igor Sieradzki
Distribution-Interpolation Trade off in Generative Models, International Conference On Learning Representations (2019),
16.
Szymon Knop, Marcin Mazur, Igor Podolak, Przemysław Spurek, Jacek Tabor
Sliced generative models, Schedae Informaticae vol. 27 (2018), 69-79
15.
Igor Podolak, Adam Roman, Marek Szykuła, Bartosz Zieliński
A machine learning approach to synchronization of automata, Expert Systems with Applications vol. 97 (2018), 357-371
14.
Wojciech Czarnecki, Igor Podolak
Adaptive Active Learning as a Multi-armed Bandit Problem, Frontiers in Artificial Intelligence and Applications vol. 263 (2014), 989-990
13.
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
12.
Wojciech Czarnecki, Igor Podolak
Machine Learning with Known Input Data Uncertainty Measure, Lecture Notes in Computer Science (2013), 379-388
11.
Igor Podolak, Adam Roman
Theoretical foundations and practical results for a hierarchical classifier with overlapping clusters, Computational Intelligence (2013), 357-388
10.
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
9.
Stanisław Brodowski, Igor Podolak
Hierarchical Estimator, Expert Systems with Applications vol. 38 (2011), 12237–12248
8.
Igor Podolak, Adam Roman
Fusion of supervised and unsupervised training methods for a multi-class classification problem, Pattern Analysis and Applications vol. 14(4) (2011), 395-413
7.
Igor Podolak, Adam Roman
Risk estimation for hierarchical classifier, Lecture Notes in Artificial Intelligence vol. 6678 (2011), 156-163
6.
Igor Podolak, Adam Roman
Risk function estimation for subproblems in a hierarchical classifier, Pattern Recognition Letters vol. 32(15) (2011), 2136-2142
5.
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
4.
Kamil Bartocha, Igor Podolak
Hierarchical Classifier with Growing Neural Gas clustering, Lecture Notes in Computer Science vol. 5495 (2009), 283-292
3.
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)
2.
Igor Podolak
Hierarchical classifier with overlapping class groups, Expert Systems with Applications vol. 1 (2008), 673-682
1.
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

Doktoranci (po 27 października 2003 roku)

DoktorantOtwarcieZakonczenie
Szymon Knop2019-04-252023-11-30
Ewa Matczyńska2014-06-262025-07-03
Igor Sieradzki2019-04-252025-07-03
Damian Leśniak2019-04-252025-07-03

Recenzje (po 27 października 2003 roku)

RecenzowanyJednostkaTreść recenzji
Doktorat: Krzysztof MisztalKatedra Uczenia Maszynowego 
Doktorat: Grzegorz JabłońskiKatedra Matematyki Obliczeniowej 

Granty (realizowane po maju 2009 roku)