prof. dr hab. Jacek Tabor

Jednostki:

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

Habilitacja  Otwarcie: 2006-04-27, Zamknięcie: 2008-06-05

Profesura  Otwarcie: 2013-05-23, Zamknięcie: 2015-07-17

Publikacje:

152.
Bartosz Zieliński, Marcin Przewięźlikowski, Mateusz Pyla, Bartłomiej Twardowski, Jacek Tabor, Marek Śmieja
Augmentation-aware self-supervised learning with conditioned projector, Knowledge-Based Systems (2024),
151.
Zięba Maciej , Marcin Przewięźlikowski, Marek Śmieja, Jacek Tabor, Tomasz Trzciński, Przemysław Spurek
RegFlow: Probabilistic Flow-Based Regression for Future Prediction, Asian Conference on Intelligent Information and Database Systems [ACIIDS], (2024), 267–279
150.
Andrzej Bedychaj, Jacek Tabor, Marek Śmieja
StyleAutoEncoder for manipulating image attributes using pre-trained StyleGAN, Pacific-Asia Conference on Knowledge Discovery and Data Mining [PAKDD], (2024), 118-130
149.
Przemysław Spurek, Marcin Przewięźlikowski, Jacek Tabor, Zięba Maciej , Przemysław Przybysz
HyperMAML: Few-shot adaptation of deep models with hypernetworks, Neurocomputing (2024), 128-179
148.
Przemysław Spurek, Wojciech Zając, Piotr Borycki, Joanna Waczyńska, Jacek Tabor, Zięba Maciej
NeRFlame: Flame-Based Conditioning of NeRF for 3D Face Rendering, International Conference on Computational Science [ICCS](MAIN) vol. 14832 (2024), 346--361
147.
Przemysław Spurek, Krzysztof Byrski, Jacek Tabor
Gaussian model for closed curves, Expert Systems with Applications vol. 249 part B (2024), 123615
146.
Bartosz Zieliński, Adriana Borowa, Dawid Rymarczyk, Marek Żyła, Marek Kańduła, Ana Sánchez-Fernández, Krzysztof Rataj, Łukasz Struski, Jacek Tabor
Decoding Phenotypic Screening: A Comparative Analysis of Image Representations, Computational and Structural Biotechnology Journal vol. 23 (2024), 1181-1188
145.
Łukasz Struski, Szymon Janusz, Jacek Tabor, Michał Markiewicz, Arkadiusz Lewicki
Multiple instance learning for medical image classification based on instance importance, Biomedical Signal Processing and Control vol. 91 (2024),
144.
Bartosz Zieliński, Mikołaj Sacha, Bartosz Jura, Dawid Rymarczyk, Łukasz Struski, Jacek Tabor
Interpretability Benchmark for Evaluating Spatial Misalignment of Prototypical Parts Explanations, National Conference of the American Association for Artificial Intelligence [AAAI](MAIN) vol. 38 (19) (2024), 21563 - 21573
143.
Adrian Suwała, Bartosz Wójcik, Magdalena Proszewska, Jacek Tabor, Przemysław Spurek, Marek Śmieja
Face Identity-Aware Disentanglement in StyleGAN, IEEE Workshop on Applications of Computer Vision [WACV], (2024), 10
142.
Łukasz Struski, Michał Sadowski, Tomasz Danel, Jacek Tabor, Igor T. 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
141.
Aleksandra Nowak, Bram Grooten, Decebal Constantin Mocanu , Jacek Tabor
Fantastic Weights and How to Find Them: Where to Prune in Dynamic Sparse Training, Advances in Neural Information Processing Systems [NeurIPS](MAIN), (2023),
140.
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
139.
Łukasz Struski, Adam Pardyl, Jacek Tabor, Bartosz Zieliński
ProPML: Probability Partial Multi-label Learning, IEEE International Conference on Data Science and Advanced Analytics [DSAA], (2023), 1-8
138.
Bartosz Zieliński, Łukasz Struski, Dawid Rymarczyk, Arkadiusz Lewicki, Robert Sabiniewicz, Jacek Tabor
ProMIL: Probabilistic Multiple Instance Learning for Medical Imaging, European Conference on Artificial Intelligence [ECAI] vol. 372 (2023), 2210 - 2217
137.
Klaudia Bałazy, Łukasz Struski, Marek Śmieja, Jacek Tabor
r-softmax: Generalized Softmax with Controllable Sparsity Rate, International Conference on Computational Science [ICCS] vol. Lecture Notes in Computer Science, vol 14074. Springer, Cham (2023), 137-145
136.
Mohammadreza Banaei, Klaudia Bałazy, Artur Kasymov, Rémi Lebret, Jacek Tabor, Karl Aberer
Revisiting Offline Compression: Going Beyond Factorization-based Methods for Transformer Language Models, European Association of Computational Linguistics [EACL] vol. Findings of the Association for Computational Linguistics: EACL 2023 (2023), 1788–1805
135.
Przemysław Spurek, Karol Piczak, Jacek Tabor, Tomasz Trzciński, Filip Szatkowski
Hypernetworks build Implicit Neural Representations of Sounds, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database [ECML PKDD] vol. 14172 (2023), 661–676
134.
Przemysław Spurek, Marcin Sendera, Marcin Przewięźlikowski, Jan Miksa, Mateusz Rajski, Konrad Karanowski, Maciej Zieba, Jacek Tabor
The general framework for few-shot learning by kernel HyperNetworks, Machine Vision and Applications vol. 34 (2023), 53
133.
Piotr Gaiński, Michał Koziarski, Jacek Tabor, Marek Śmieja
ChiENN: Embracing Molecular Chirality with Graph Neural Networks, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database [ECML PKDD] vol. Lecture Notes in Computer Science(), vol 14171. Springer, Cham (2023), 36-52
132.
Michał Znaleźniak, Przemysław Rola, Patryk Kaszuba, Jacek Tabor, Marek Śmieja
Contrastive Hierarchical Clustering, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database [ECML PKDD] vol. Lecture Notes in Computer Science(), vol 14169. Springer, Cham. (2023), 627–643
131.
Łukasz Struski, Marcin Mazur, Paweł Batorski, Przemysław Spurek, Jacek Tabor
Bounding Evidence and Estimating Log-Likelihood in VAE, International Conference on Artificial Intelligence and Statistics [AISTATS](MAIN) vol. 206 (2023), 5036-5051
130.
Przemysław Spurek, Jacek Tabor, Marcin Sendera, Marcin Przewięźlikowski, Konrad Karanowski, Zięba Maciej
Hypershot: Few-shot learning by kernel hypernetworks, IEEE Workshop on Applications of Computer Vision [WACV](MAIN), (2023), 2469--2478
129.
Mikołaj Sacha, Dawid Rymarczyk, Łukasz Struski, Jacek Tabor, Bartosz Zieliński
ProtoSeg: Interpretable Semantic Segmentation with Prototypical Parts, IEEE Workshop on Applications of Computer Vision [WACV](MAIN) vol. 2023 (2023), 1481-1492
128.
Łukasz Struski, Tomasz Danel, Marek Śmieja, Jacek Tabor, Bartosz Zieliński
SONGs: Self-Organizing Neural Graphs, IEEE Workshop on Applications of Computer Vision [WACV](MAIN), (2023), 3837-3846
127.
Bartosz Wójcik, Jacek Grela, Marek Śmieja, Krzysztof Misztal, Jacek Tabor
SLOVA: Uncertainty estimation using single label one-vs-all classifier, Applied Soft Computing Journal vol. 126 (2022), 109219
126.
Jacek Tabor, Marek Śmieja, Łukasz Struski, Przemysław Spurek, Maciej Wołczyk
Głębokie uczenie. Wprowadzenie, Helion, 2022
125.
Przemysław Spurek, Artur Kasymov, Marcin Mazur, Diana Janik, Sławomir K. Tadeja, Łukasz Struski, Jacek Tabor, Tomasz Trzciński
HyperPocket: generative point cloud completion, IEEE/RSJ International Conference on Intelligent Robots and Systems [IROS], (2022), 6848-6853
124.
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
123.
Andrzej Bedychaj, Przemysław Spurek, Aleksandra Nowak, Jacek Tabor
Nonlinear Weighted Independent Component Analysis, International Conference on Information Processing and Management of Uncertainty [IPMU] vol. II (2022), 3–16
122.
Przemysław Spurek, Jacek Tabor, Piotr Tempczyk, Rafał Michaluk, Łukasz Garncarek, Adam Golinski
LIDL: Local Intrinsic Dimension Estimation Using Approximate Likelihood, International Conference on Machine Learning [ICML](MAIN), (2022), 21205-21231
121.
Jacek Tabor, Maciej Wołczyk, Karol Piczak, Bartosz Wójcik, Łukasz Pustelnik, Morawiecki Paweł, Tomasz Trzcinski, Przemysław Spurek
Continual Learning with Guarantees via Weight Interval Constraints, International Conference on Machine Learning [ICML](MAIN), (2022), 23897-23911
120.
Dawid Rymarczyk, Łukasz Struski, Michał Górszczak, Koryna Lewandowska, Jacek Tabor, Bartosz Zieliński
Interpretable Image Classification with Differentiable Prototypes Assignment, European Conference on Computer Vision [ECCV](MAIN) vol. Lecture Notes in Computer Science 13672 (2022), 351-368
119.
Łukasz Struski, Szymon Knop, Jacek Tabor, Daniec Wiktor , Przemysław Spurek
LocoGAN—Locally convolutional GAN, Computer Vision and Image Understanding vol. 221 (2022), 103462
118.
Adriana Borowa, Szczepan Kruczek, Jacek Tabor, Bartosz Zieliński
Weakly-supervised cell classification for effective High Content Screening, International Conference on Computational Science [ICCS](MAIN) vol. Lecture Notes in Computer Science 13350 (2022), 318–330
117.
Szymon Knop, Marcin Mazur, Igor Podolak, Przemysław Spurek, Jacek Tabor
Generative models with kernel distance in data space, Neurocomputing vol. 487 (2022), 119-129
116.
Marcin Przewięźlikowski, Marek Śmieja, Łukasz Struski, Jacek Tabor
MisConv: Convolutional Neural Networks for Missing Data, IEEE Workshop on Applications of Computer Vision [WACV], (2022), 2060-2069
115.
Łukasz Struski, Jacek Tabor, Szymon Bobek, Sławomir K. Tadeja, Przemysław Stachura, Timoleon Kipourus, Grzegorz Nalepa, Per Ola Kristensson
Virtual Reality-Based Parallel Coordinates Plots Enhanced with Explainable AI and Data-Science Analytics for Decision-Making Processes, Applied Sciences-Basel vol. 12, 1 (2022), 331
114.
Łukasz Maziarka, Marek Śmieja, Marcin Sendera, Łukasz Struski, Jacek Tabor, Przemysław Spurek
OneFlow: One-class flow for anomaly detection based on a minimal volume region, IEEE Transactions on Pattern Analysis and Machine Intelligence vol. 44/11 (2022), 8508-8519
113.
Zięba Maciej , Przemysław Spurek, Jacek Tabor, Tomasz Trzciński
General hypernetwork framework for creating 3D point clouds, IEEE Transactions on Pattern Analysis and Machine Intelligence vol. 44 (2021), 9995-10008
112.
Bartosz Wójcik, Morawiecki Paweł, Marek Śmieja, Tomasz Krzyżek, Przemysław Spurek, Jacek Tabor
Adversarial Examples Detection and Analysis with Layer-wise Autoencoders, International Conference on Tools with Artificial Intelligence [ICTAI], (2021), 1322-1326
111.
Marcin Sendera, Jacek Tabor, Aleksandra Nowak, Andrzej Bedychaj, Massimiliano Patacchiola, Przemysław Spurek, Tomasz Trzciński, Zięba Maciej
Non-Gaussian Gaussian Processes for Few-Shot Regression, Advances in Neural Information Processing Systems [NeurIPS](MAIN) vol. 34 (2021), 10285-10298
110.
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
109.
Karl Aberer, Klaudia Bałazy, Mohammadreza Banaei, Rémi Lebret, Jacek Tabor
Direction is what you need: Improving Word Embedding Compression in Large Language Models, Proceedings of the 6th Workshop On Representation Learning for Nlp (repl4nlp-2021) (2021), 322–330
108.
Tomasz Danel, Łukasz Maziarka, Sabina Podlewska, Jacek Tabor, Agnieszka Wojtuch
Comparison of Atom Representations in Graph Neural Networks for Molecular Property Prediction, IEEE International Joint Conference on Neural Networks [IJCNN], (2021), 1-8
107.
Dawid Rymarczyk, Łukasz Struski, Jacek Tabor, Bartosz Zieliński
ProtoPShare: Prototypical Parts Sharing for Similarity Discovery in Interpretable Image Classification, ACM International Conference on Knowledge Discovery and Data Mining [KDD](MAIN) vol. 9781450383325 (2021), 1420-1430
106.
Adriana Borowa, Dawid Rymarczyk, Jacek Tabor, Bartosz Zieliński
Kernel Self-Attention for Weakly-supervised Image Classification using Deep Multiple Instance Learning, IEEE Workshop on Applications of Computer Vision [WACV] vol. 978-1-6654-0477-8 (2021), 1720-1729
105.
Bernhard C. Geiger, Marek Śmieja, Jacek Tabor, Maciej Wołczyk
SeGMA: Semi-Supervised Gaussian Mixture Autoencoder, IEEE Transactions on Neural Networks and Learning Systems vol. 32/9 (2021), 3930-3941
104.
Andrzej Bojarski, Stanisław Jastrzębski, Stefan Mordalski, Sabina Podlewska, Maciej Szymczak, Jacek Tabor, Agnieszka Wojtuch
Emulating docking results using a deep neural network: a new perspective for virtual screening, Journal of Chemical Information and Modeling (2020), 4246-4262
103.
Morawiecki Paweł, Przemysław Spurek, Marek Śmieja, Jacek Tabor
Fast and Stable Interval Bounds Propagation for Training Verifiably Robust Models, European Symposium on Artificial Neural Networks [ESANN], (2020), 6
102.
Tomasz Danel, Przemysław Spurek, Jacek Tabor, Marek Śmieja, Łukasz Struski, Agnieszka Słowik, Łukasz Maziarka
Spatial Graph Convolutional Networks, International Conference On Neural Information Processing vol. Communications in Computer and Information Science book series (CCIS, volume 1333) (2020), 668-675
101.
Stanisław Jastrzębski, Łukasz Maziarka, Aleksandra Nowak, Przemysław Spurek, Jacek Tabor
Non-linear ICA based on Cramer-Wold metric, International Conference On Neural Information Processing vol. Lecture Notes in Computer Science book series (LNCS, volume 12534) (2020),
100.
Zięba Maciej , Przemysław Spurek, Jacek Tabor, Tomasz Trzciński, Sebastian Winczowski, Maciej Zamorski
Hypernetwork approach to generating point clouds, International Conference on Machine Learning [ICML](MAIN), (2020),
99.
Klaudia Bałazy, Jacek Tabor, Maciej Wołczyk, Bartosz Wójcik
Finding the Optimal Network Depth in Classification Tasks, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database (PKDD and ECML combined from 2008) [ECML PKDD], (2020),
98.
Devansh Arpit, Kyunghyun Cho, Stanislav Fort, Krzysztof J. Geras, Stanisław Jastrzębski, Maciej Szymczak, Jacek Tabor
The Break-Even Point on Optimization Trajectories of Deep Neural Networks, 8th International Conference On Learning Representations (2020),
97.
Andrzej Bojarski, Stanisław Jastrzębski, Stefan Mordalski, Sabina Podlewska, Maciej Szymczak, Jacek Tabor, Agnieszka Wojtuch
Emulating Docking Results Using a Deep Neural Network: A New Perspective for Virtual Screening, Journal of Chemical Information and Modeling vol. 60 (2020), 4246-4262
96.
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
95.
Marcin Sendera, Marek Śmieja, Łukasz Maziarka, Łukasz Struski, Przemysław Spurek, Jacek Tabor
Flow-based SVDD for anomaly detection, International Conference On Machine Learning (workshop Track) (2020),
94.
Łukasz Struski, Marek Śmieja, Jacek Tabor
Pointed subspace approach to incomplete data, Journal of Classification vol. 37 (2020), 42-57
93.
Stanisław Jastrzębski, Maciej A. Nowak, Jacek Tabor, Wojciech Tarnowski, Piotr Warchoł
Dynamical Isometry is Achieved in Residual Networks in a Universal Way for any Activation Function, International Conference on Artificial Intelligence and Statistics [AISTATS], (2019), 10
92.
Andrzej Bojarski, Stanisław Jastrzębski, Damian Leśniak, Sabina Podlewska, Igor Sieradzki, Jacek Tabor
Development of New Methods Needs Proper Evaluation -- Benchmarking Sets for Machine Learning Experiments for Class A GPCRs, Journal of Chemical Information and Modeling vol. 59 (2019), 4974-4992
91.
Marek Śmieja, Łukasz Struski, Jacek Tabor, Mateusz Marzec
Generalized RBF kernel for incomplete data, Knowledge-Based Systems vol. 173 (2019), 150-162
90.
Szymon Maszke, Marek Śmieja, Jacek Tabor, Maciej Wołczyk
Biologically-Inspired Spatial Neural Networks, (2019), 5
89.
Łukasz Maziarka, Marek Śmieja, Aleksandra Nowak, Jacek Tabor, Łukasz Struski, Przemysław Spurek
Set Aggregation Network as a Trainable Pooling Layer, International Conference On Neural Information Processing vol. Lecture Notes in Computer Science book series (LNCS, volume 11954) (2019), 419-431
88.
Tomasz Danel, Stanisław Jastrzębski, Łukasz Maziarka, Sławomir Mucha, Krzysztof Rataj, Jacek Tabor
Molecule-Augmented Attention Transformer, Neural Information Processing Systems (workshop Track) (2019),
87.
Sylwester Klocek, Łukasz Maziarka, Jakub Nowak, Marek Śmieja, Jacek Tabor, Maciej Wołczyk
Hypernetwork Functional Image Representation, Artificial Neural Networks and Machine Learning – Icann 2019: Workshop and Special Sessions (2019), 496-510
86.
Krzysztof Hajto, Marek Śmieja, Jacek Tabor
Efficient mixture model for clustering of sparse high dimensional binary data, Data Mining and Knowledge Discovery vol. 33/6 (2019), 1583-1624
85.
Łukasz Struski, Przemysław Spurek, Jacek Tabor, Marek Śmieja
Projected memory clustering, Pattern Recognition Letters vol. 123 (2019), 9-15
84.
Krzysztof Byrski, Przemysław Spurek, Jacek Tabor
Online updating of active function cross-entropy clustering, Pattern Analysis and Applications vol. vol. 22 no. 4 (2019), 1409-1425
83.
Przemysław Spurek, Marek Śmieja, Jacek Tabor
SVM with a neutral class, Pattern Analysis and Applications vol. 22/2 (2019), 573-582
82.
Andrzej Bojarski, Stanisław Jastrzębski, Damian Leśniak, Sabina Podlewska, Igor Sieradzki, Jacek Tabor
Three-dimensional descriptors for aminergic GPCRs: dependence on docking conformation and crystal structure, Molecular Diversity vol. vol.23 no.3 (2018), 603-613
81.
Łukasz Maziarka, Jacek Tabor, Bartosz Wójcik
LOSSGRAD: Automatic Learning Rate in Gradient Descent, Schedae Informaticae vol. 27 (2018), 47-57
80.
Krzysztof Misztal, Przemysław Spurek, Jacek Tabor
Image Stitching Based on Entropy Minimization, Schedae Informaticae vol. 27 (2018), 129-141
79.
Szymon Knop, Marcin Mazur, Igor Podolak, Przemysław Spurek, Jacek Tabor
Sliced generative models, Schedae Informaticae vol. 27 (2018), 69-79
78.
Przemysław Spurek, Jacek Tabor, Łukasz Struski, Marek Śmieja
Fast independent component analysis algorithm with a simple closed-form solution, Knowledge-Based Systems vol. 161 (2018), 26-34
77.
Marek Śmieja, Łukasz Struski, Jacek Tabor, Bartosz Zieliński, Przemysław Spurek
Processing of missing data by neural networks, Advances in Neural Information Processing Systems vol. 31 (2018), 2719-2729
76.
Oleksandr Myronov, Marek Śmieja, Jacek Tabor
Semi-supervised discriminative clustering with graph regularization, Knowledge-Based Systems vol. 151 (2018), 24-36
75.
Łukasz Struski, Jacek Tabor, Przemysław Spurek
Lossy Compression Approach to Subspace Clustering, Information Sciences vol. 435 (2018), 161-183
74.
Łukasz Struski, Jacek Tabor
Expansivity implies existence of Holder continuous Lyapunov function, Discrete and Continuous Dynamical Systems - Series B vol. 22 (9) (2017), 3575-3589
73.
Łukasz Struski, Marek Śmieja, Bartosz Zieliński, Jacek Tabor
Regression SVM for incomplete data, Schedae Informaticae vol. 26 (2017), 23-35
72.
Wojciech Czarnecki, Stanisław Jastrzębski, Damian Leśniak
How to evaluate word embeddings? On importance of data efficiency and simple supervised tasks, Arxiv (2017),
71.
Michał Ociepka, Przemysław Rola, Przemysław Spurek, Jacek Tabor
ICA based on asymmetry, Pattern Recognition vol. 67 (2017), 230-244
70.
Krzysztof Byrski, Przemysław Spurek, Jacek Tabor
Active Function Cross-Entropy Clustering, Expert Systems with Applications vol. 72 (2017), 49–66
69.
Konrad Kamieniecki, Krzysztof Misztal, Przemysław Spurek, Marek Śmieja, Jacek Tabor
R Package CEC , Neurocomputing vol. 237 (2017), 410–413
68.
Wojciech Czarnecki, Jacek Tabor
Extreme entropy machines: robust information theoretic classification, Pattern Analysis and Applications vol. 20 (2017), 383–400
67.
Marek Śmieja, Łukasz Struski, Jacek Tabor
Semi-supervised model-based clustering with controlled clusters leakage, Expert Systems with Applications vol. 85 (2016), 146-157
66.
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
65.
Przemysław Spurek, Jacek Tabor
Maximum Likelihood Estimation and Optimal Coordinates, International Conference On Systems Science, 2016 vol. Springer (2016), 3-13
64.
Jakub Hyła, Krzysztof Misztal, Jacek Tabor
Optimal Ellipse Based Algorithm as an Approximate and Robust Solution of Minimum Volume Covering Ellipse Problem, Lecture Notes in Computer Science vol. 9842 (2016), 240-250
63.
Wojciech Czarnecki, Jacek Tabor
Online Extreme Entropy Machines for Streams Classification and Active Learning, Advances in Intelligent Systems and Computing vol. 403 (2016), 371-381
62.
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
61.
Krzysztof Misztal, Jacek Tabor
Ellipticity and circularity measuring via Kullback-Leibler divergence, Journal of Mathematical Imaging and Vision vol. 55 (1) (2016), 136-150
60.
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
59.
Jacek Chudziak, Jacek Tabor, Józef Tabor
Conditionally d-midconvex functions, Aequationes Mathematicae vol. 89 (2015), 981-990
58.
Mateusz Malik, Przemysław Spurek, Jacek Tabor
Cross-Entropy based image thresholding, Schedae Informaticae vol. 24 (2015), 21-29
57.
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
56.
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
55.
Łukasz Struski, Jacek Tabor, Przemysław Spurek
Subspace memory clustering, Schedae Informaticae vol. 24 (2015), 133-142
54.
Wojciech Czarnecki, Rafał Józefowicz, Jacek Tabor
Maximum Entropy Linear Manifold for Learning Discriminative Low-dimensional Representation, Lecture Notes in Artificial Intelligence vol. 9284 (2015), 52-67
53.
Przemysław Spurek, Jacek Tabor, Mateusz Wójcik
Cross-Entropy Clustering Approach to One-Class Classification, Lecture Notes in Computer Science vol. 9119 (2015), 481-490
52.
Marek Śmieja, Jacek Tabor
Entropy approximation in lossy source coding problem, Entropy vol. 17/5 (2015), 3400-3418
51.
Marek Śmieja, Magdalena Wiercioch
Mixture of metrics optimization for machine learning problems, Schedae Informaticae vol. 24 (2015), 133-142
50.
Wojciech Czarnecki, Jacek Tabor
Multithreshold Entropy Linear Classifier: Theory and Applications, Expert Systems with Applications vol. 42 (2015), 5591-5606
49.
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
48.
Łukasz Struski, Jacek Tabor
Expansivity and Cone-fields in Metric Spaces, Journal of Dynamics and Differential Equations vol. 26(3) (2014), 517-527
47.
Wojciech Czarnecki, Jacek Tabor
Two ellipsoid Support Vector Machines, Expert Systems with Applications vol. 41 (18) (2014), 8211-8224
46.
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
45.
Przemysław Spurek, Jacek Tabor
Cross Entropy Clustering, Pattern Recognition vol. 47 (2014), 3046–3059
44.
Marek Śmieja, Jacek Tabor
Renyi entropy dimension of the mixture of measures, Proceedings of Science and Information Conference (2014), 685-689
43.
Krzysztof Misztal, Jacek Tabor, Józef Tabor
Generalized midconvexity, Banach Center Publications vol. 99 (2013), 207-215
42.
Krzysztof Misztal, Jacek Tabor
Detection of elliptical shapes via cross-entropy clustering, Pattern Recognition and Image Analysis Lecture Notes in Computer Science vol. 7887 (2013), 656-663
41.
Krzysztof Misztal, Jacek Tabor
Mahalanobis distance-based algorithm for ellipse growing in iris preprocessing, Computer Information Systems and Industrial Management Lecture Notes in Computer Science vol. 8104 (2013), 158-167
40.
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
39.
Jacek Tabor, Józef Tabor, Marek Żołdak
Strongly Midquasiconvex Functions , Journal of Convex Analysis vol. 20 (2013), 531-543
38.
Przemysław Spurek, Jacek Tabor
The memory center, Information Sciences vol. 252 (2013), 132–143
37.
Marek Śmieja, Jacek Tabor
Image segmentation with use of cross-entropy clustering, Advances in Intelligent Systems and Computing vol. 226 (2013), 403-409
36.
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
35.
Krzysztof Misztal, Jacek Tabor, Józef Tabor
Midconvexity for finite sets, Journal of Inequalities and Applications vol. 2013 (2013), 1-16
34.
Krzysztof Misztal, Jacek Tabor
Strict verification of approximate midconvexity on non-convex sets, Mathematical Inequalities and Applications vol. 16 (2013), 389–400
33.
Jacek Tabor, Józef Tabor
Paraconvex, but not strongly, Takagi functions, Control and Cybernetics vol. 41 (2012), 545-559
32.
Piotr Kościelniak, Marcin Mazur, Jacek Tabor
Appendix A: Semi-Hyperbolicity: Estimations vol. Random and Computational Dynamics 1 (2012), "Phil Diamond, Peter Kloeden, Victor Kozyakin, Alexei Pokrovskii, Semi-Hyperbolicity and Bi-Shadowing", American Institute of Mathematical Sciences
31.
Anna Mureńko, Jacek Tabor, Józef Tabor
Applications of de Rham theorem in approximate midconvexity, Journal of Difference Equations and Applications vol. 18 (2012), 335-344
30.
Przemysław Spurek, Jacek Tabor
Numerical verification of condition for approximately midconvex functions, Aequationes Mathematicae vol. 83 (2012), 223-237
29.
Łukasz Struski, Jacek Tabor, Tomasz Kulaga
Cone-Fields without Constant Orbit Core Dimension, Discrete and Continuous Dynamical Systems vol. 32(10) (2012), 3651-3664
28.
Krzysztof Misztal, Khalid Saeed, Jacek Tabor
A new algorithm for rotation detection in iris pattern recognition, Lecture Notes in Computer Science vol. Computer Information Systems and Industrial Management, Volume 7564/2012 (2012), 135-145
27.
Jakub Bielawski, Jacek Tabor
A t-norm embedding theorem for fuzzy sets, Fuzzy Sets and Systems (2012), 33-53
26.
Krzysztof Misztal, Emil Saeed, Khalid Saeed, Jacek Tabor
Iris Pattern Recognition with a New Mathematical Model to its Rotation Detection vol. 1 (2012), "Biometrics and Kansei Engineering", Springer Verlag (połaczony z Kluwer Academic Publishing)
25.
Krzysztof Misztal, Jacek Tabor, Józef Tabor
Approximately Midconvex Functions vol. Springer Optimization and Its Applications (2012), "Functional Equations in Mathematical Analysis", Springer Verlag (połaczony z Kluwer Academic Publishing)
24.
Marek Śmieja, Jacek Tabor
Entropy of the mixture of source and entropy dimension, IEEE Transactions on Information Theory vol. 58(5) (2012), 2719-2728
23.
Jacek Tabor, Józef Tabor, Marek Żołdak
On w-strongly quasiconvex and w-strongly quasiconcave sequences, Aequationes Mathematicae vol. 82 (2011), 255-268
22.
Anna Mureńko, Jacek Tabor, Józef Tabor
Semiconcave functions with power moduli, Journal of Convex Analysis vol. 18 (2011), 391-396
21.
Tomasz Kułaga, Jacek Tabor
Hyperbolic dynamics in graph-directed IFS, Journal of Differential Equations vol. 251 (2011), 3363-3380
20.
Marcin Mazur, Jacek Tabor
Computational hyperbolicity, Discrete and Continuous Dynamical Systems vol. 29 (2011), 1175-1189
19.
Jacek Tabor, Józef Tabor, Marek Żołdak
Optimality estimations for approximately convex functions, Aequationes Mathematicae vol. 80 (2010), 227-237
18.
Adam Najdecki, Jacek Tabor, Józef Tabor
On conditionally d-convex functions, Acta Mathematica Hungarica vol. 128 (2010), 131-138
17.
Jacek Tabor, Józef Tabor, Marek Żołdak
Approximately convex functions on topological vector spaces, Publicationes Mathematicae vol. 365 (2010), 115-123
16.
Jacek Tabor, Józef Tabor
Extensions of convex and semiconvex functions and intervally thin sets, Journal of Mathematical Analysis and Applications vol. 365 (2010), 43-49
15.
Jacek Mrowiec, Jacek Tabor, Józef Tabor
Approximately midconvex functions vol. International Series of Numerical Mathematics 157 (2009), "Inequalities and Applications", Birkhäuser
14.
Anna Mureńko, Jacek Tabor, Józef Tabor
On characterizations of sup-preserving functionals, Acta Mathematica Hungarica vol. 12 (2009), 161-172
13.
Jacek Tabor, Józef Tabor
Takagi functions and approximate midconvexity, Journal of Mathematical Analysis and Applications vol. 356 (2009), 729-737
12.
Jacek Tabor, Józef Tabor
Characterization of convex functions, Studia Mathematica vol. 192 (2009), 29-37
11.
Jacek Tabor, Józef Tabor
Generalized approximate midconvexity, Control and Cybernetics vol. 38 (2009), 655-669
10.
Jakub Bielawski, Jacek Tabor
An embedding theorem for unbounded convex sets in a Banach space, Demonstratio Mathematica vol. 42(4) (2009), 703-709
9.
Jacek Tabor
Stability of isometries in p-Banach spaces, Functiones et Approximatio, Commentarii Mathematici vol. 38 (2008), 109-119
8.
Jacek Tabor, Józef Tabor
Stability of the Cauchy functional equations in metric groupoids, Aequationes Mathematicae vol. 76 (2008), 92-104
7.
Jacek Tabor
Restricted stability and shadowing, Publicationes Mathematicae vol. 73 (2008), 49-58
6.
Piotr Kościelniak, Marcin Mazur, Jacek Tabor
Semi-hyperbolicity and hyperbolicity, Discrete and Continuous Dynamical Systems (2008), 1029-1038
5.
Bogdan Batko, Zygfryd Kominek, Jacek Tabor
Generalized norms and convexity, Publicationes Mathematicae vol. 60.1-2 (2002), 63-73
4.
Marcin Kulczycki, Jacek Tabor
Iterative functional equations in the class of Lipschitz functions, Aequationes Mathematicae vol. 64, no. 1-2 (2002), 24-33
3.
Bogdan Batko, Jacek Tabor
Stability of an alternative Cauchy equation on a restricted, Aequationes Mathematicae vol. 57 (1999), 221-232
2.
Bogdan Batko, Jacek Tabor
Stability of the generalized alternative Cauchy equation , Abhandlungen aus dem Mathematischen Seminar der Universitat Hamburg vol. 69 (1999), 67-73
1.
Marcin Mazur, Kinga Stolot, Jacek Tabor
Semi-hyperbolicity implies hyperbolicity in the linear case, Universitatis Iagellonicae Acta Mathematica vol. 36 (1998), 121-126

Konferencje organizowane:

2.
Jacek Tabor.
Deep Learning Workshops, Kraków, 2018-02-20, 2018-02-23
1.
Jacek Tabor.
Theoretical Foundations of Machine Learning (TFML 2019) , Kraków, 2019-02-11, 2019-02-15

Doktoranci (po 27 października 2003 roku)

DoktorantOtwarcieZakonczenie
Tomasz Kulaga2009-06-252012-10-25
Jakub Bielawski2010-06-242013-04-25
Krzysztof Misztal2011-05-262015-04-30
Przemysław Spurek2012-05-312014-06-26
Łukasz Struski2012-05-312014-01-30
Łukasz Struski2013-03-282014-01-30
Marek Śmieja2013-06-272015-01-29
Wojciech Czarnecki2014-06-262015-12-17
Magdalena Wiercioch2016-06-30 
Stanisław Jastrzębski2017-06-292019-03-28
Andrzej Bedychaj2020-09-24 

Recenzje (po 27 października 2003 roku)

RecenzowanyJednostkaTreść recenzji
Doktorat: Natalia ŻelaznaKatedra Matematyki Obliczeniowej 
Doktorat: Krzysztof WesołowskiKatedra Teorii Aproksymacji 

Granty (realizowane po maju 2009 roku)

TytułRolaRozpoczęcieZakończenie
Meta-uczenie w głębokich sieciach neuronowychKierownik2024-01-292028-01-28
Głębokie samoorganizujące się grafy neuronoweKierownik2022-02-042025-02-03
Sztuczne sieci neuronowe inspirowane biologicznieKierownik2019-09-012023-11-29
Efektywne metody uczenia nienadzorowanego z zastosowaniami w głębokim nauczaniuKierownik2018-02-092021-02-08
Teoria analizy niekompletnych danychKierownik2016-07-132019-10-12
Paradygmat minimalizacji pamięci w klastrowaniuKierownik2015-01-212017-08-26
Uogólnienie entropii i wymiaru entropijnego oraz ich zastosowaniaKierownik2011-12-082014-12-07