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:
168.
Classifier-Free Guidance with Adaptive Scaling, European Conference on Artificial Intelligence [ECAI] vol. 413 (2025), 435 - 442
167.
Adam Kania, Marko Mihajlovic, Prokudin Sergey, Jacek Tabor, Przemysław Spurek
FreSh: Frequency Shifting for Accelerated Neural Representation Learning, International Conference on Learning Representations [ICLR] vol. 9798331320850 (2025), 1-24
166.
Piotr Gaiński, Michał Koziarski, Krzysztof Maziarz, Marvin Segler, Jacek Tabor, Marek Śmieja
Diverse and feasible retrosynthesis using gflownets, Information Sciences vol. 714 (2025), 122194
165.
PrAViC: Probabilistic Adaptation Framework for Real-Time Video Classification, European Conference on Artificial Intelligence [ECAI](MAIN), (2025), accepted
164.
LapSum - One Method to Differentiate Them All: Ranking, Sorting and Top-k Selection, International Conference on Machine Learning [ICML], (2025),
163.
Łukasz Struski, Tomasz Urbańczyk, Krzysztof Bucki, Bartłomiej Cupiał, Aneta Kaczyńska, Przemysław Spurek, Jacek Tabor
MeVGAN: GAN-based plugin model for video generation with applications in colonoscopy, PLoS One vol. 20 (5) (2025), e0312038
162.
SEMU: Singular Value Decomposition for Efficient Machine Unlearning, International Conference on Machine Learning [ICML], (2025),
161.
Hypernetwork Approach to Bayesian MAML (Student Abstract), National Conference of the American Association for Artificial Intelligence [AAAI] vol. 39 (2025), 29325-29327
160.
Mateusz Poleski, Jacek Tabor, Przemysław Spurek
GeoGuide: Geometric Guidance of Diffusion Models, IEEE Workshop on Applications of Computer Vision [WACV](MAIN) vol. 1 (2025), 297-305
159.
CEC-MMR: Cross-Entropy Clustering Approach to Multi-Modal Regression, IEEE International Joint Conference on Neural Networks [IJCNN](MAIN), (2025), accepted
158.
Dominik Zimny, Artur Kasymov, Adam Kania, Jacek Tabor, Maciej Zięba, Marcin Mazur, Przemysław Spurek
MultiPlaneNeRF: Neural Radiance Field with Non-Trainable Representation, Expert Systems with Applications vol. 279 (2025), 127350
157.
VisTabNet: Adapting Vision Transformers for Tabular Data, SIAM International Conference on Data Mining [SDM], (2025), 10
156.
NegGS: Negative Gaussian Splatting, Information Sciences vol. 702 (2025), 121912
155.
LucidPPN: Unambiguous Prototypical Parts Network for User-centric Interpretable Computer Vision, International Conference on Learning Representations [ICLR](MAIN) vol. ICLR 2025 200 pkt (2025), 1-97
154.
Gaussian Splatting with NeRF-based color and opacity, Computer Vision and Image Understanding vol. 251 (2025), 104273
153.
Aleksandra Nowak, Łukasz Gniecki, Filip Szatkowski, Jacek Tabor
Sparser, Better, Deeper, Stronger: Improving Static Sparse Training with Exact Orthogonal Initialization, International Conference on Machine Learning [ICML] vol. Proceedings of Machine Learning Research, Volume 235 (2024), 38474--38494
152.
Bartosz Zieliński, Marcin Przewięźlikowski, Mateusz Pyla, Bartłomiej Twardowski, Jacek Tabor, Marek Śmieja
Augmentation-aware self-supervised learning with conditioned projector, Knowledge-Based Systems vol. 305 (2024), 112572
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.
Marcin Przewięźlikowski, Przemysław Przybysz, Zięba Maciej , Jacek Tabor, Przemysław Spurek
HyperMAML: Few-shot adaptation of deep models with hypernetworks, Neurocomputing vol. 598 (2024), 128-179
148.
NeRFlame: Flame-Based Conditioning of NeRF for 3D Face Rendering, International Conference on Computational Science [ICCS](MAIN) vol. 14832 (2024), 346--361
147.
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
145.
144.
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.
Face Identity-Aware Disentanglement in StyleGAN, IEEE Workshop on Applications of Computer Vision [WACV], (2024), 5222-5231
142.
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) vol. Advances in Neural Information Processing Systems 36 (NeurIPS 2023) (2023), 55160--55192
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.
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.
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.
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
133.
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.
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.
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.
ProtoSeg: Interpretable Semantic Segmentation with Prototypical Parts, IEEE Workshop on Applications of Computer Vision [WACV](MAIN) vol. 2023 (2023), 1481-1492
128.
SONGs: Self-Organizing Neural Graphs, IEEE Workshop on Applications of Computer Vision [WACV](MAIN), (2023), 3837-3846
127.
SLOVA: Uncertainty estimation using single label one-vs-all classifier, Applied Soft Computing Journal vol. 126 (2022), 109219
126.
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.
Batch size reconstruction-distribution trade-off in kernel based generative autoencoders, IEEE International Conference on Image Processing [ICIP], (2022), 3728-3732
123.
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.
LocoGAN—Locally convolutional GAN, Computer Vision and Image Understanding vol. 221 (2022), 103462
118.
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.
Generative models with kernel distance in data space, Neurocomputing vol. 487 (2022), 119-129
116.
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
114.
113.
Zięba Maciej , Przemysław Spurek, Jacek Tabor, Tomasz Trzciński
112.
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.
Comparison of Atom Representations in Graph Neural Networks for Molecular Property Prediction, IEEE International Joint Conference on Neural Networks [IJCNN], (2021), 1-8
107.
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.
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.
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
103.
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.
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.
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
96.
Cramer-Wold Auto-Encoder, Journal of Machine Learning Research vol. 21 (2020), 1-28
95.
Flow-based SVDD for anomaly detection, International Conference On Machine Learning (workshop Track) (2020),
94.
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
91.
Generalized RBF kernel for incomplete data, Knowledge-Based Systems vol. 173 (2019), 150-162
90.
89.
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.
Hypernetwork Functional Image Representation, Artificial Neural Networks and Machine Learning – Icann 2019: Workshop and Special Sessions (2019), 496-510
86.
85.
Projected memory clustering, Pattern Recognition Letters vol. 123 (2019), 9-15
84.
Online updating of active function cross-entropy clustering, Pattern Analysis and Applications vol. vol. 22 no. 4 (2019), 1409-1425
83.
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.
Image Stitching Based on Entropy Minimization, Schedae Informaticae vol. 27 (2018), 129-141
79.
Sliced generative models, Schedae Informaticae vol. 27 (2018), 69-79
78.
77.
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.
Lossy Compression Approach to Subspace Clustering, Information Sciences vol. 435 (2018), 161-183
74.
73.
Regression SVM for incomplete data, Schedae Informaticae vol. 26 (2017), 23-35
72.
Wojciech Czarnecki, Stanisław Jastrzębski, Damian Leśniak
71.
ICA based on asymmetry, Pattern Recognition vol. 67 (2017), 230-244
70.
Active Function Cross-Entropy Clustering, Expert Systems with Applications vol. 72 (2017), 49–66
69.
R Package CEC , Neurocomputing vol. 237 (2017), 410–413
68.
67.
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.
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.
Online Extreme Entropy Machines for Streams Classification and Active Learning, Advances in Intelligent Systems and Computing vol. 403 (2016), 371-381
62.
61.
60.
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.
Cross-Entropy based image thresholding, Schedae Informaticae vol. 24 (2015), 21-29
57.
56.
Spherical Wards clustering and generalized Voronoi diagrams, Proceeding of Ieee International Conference On Data Science and Advanced Analytics vol. 36678 (2015), 10
55.
Subspace memory clustering, Schedae Informaticae vol. 24 (2015), 133-142
54.
Wojciech Czarnecki, Rafał Józefowicz, Jacek Tabor
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.
Entropy approximation in lossy source coding problem, Entropy vol. 17/5 (2015), 3400-3418
51.
Mixture of metrics optimization for machine learning problems, Schedae Informaticae vol. 24 (2015), 133-142
50.
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.
Expansivity and Cone-fields in Metric Spaces, Journal of Dynamics and Differential Equations vol. 26(3) (2014), 517-527
47.
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.
Cross Entropy Clustering, Pattern Recognition vol. 47 (2014), 3046–3059
44.
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.
Detection of elliptical shapes via cross-entropy clustering, Pattern Recognition and Image Analysis Lecture Notes in Computer Science vol. 7887 (2013), 656-663
41.
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.
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.
The memory center, Information Sciences vol. 252 (2013), 132–143
37.
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.
33.
Jacek Tabor, Józef Tabor
Paraconvex, but not strongly, Takagi functions, Control and Cybernetics vol. 41 (2012), 545-559
32.
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
30.
29.
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.
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.
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
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.
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.
Restricted stability and shadowing, Publicationes Mathematicae vol. 73 (2008), 49-58
6.
5.
Bogdan Batko, Zygfryd Kominek, Jacek Tabor
Generalized norms and convexity, Publicationes Mathematicae vol. 60.1-2 (2002), 63-73
4.
Iterative functional equations in the class of Lipschitz functions, Aequationes Mathematicae vol. 64, no. 1-2 (2002), 24-33
3.
Stability of an alternative Cauchy equation on a restricted, Aequationes Mathematicae vol. 57 (1999), 221-232
2.
1.
Semi-hyperbolicity implies hyperbolicity in the linear case, Universitatis Iagellonicae Acta Mathematica vol. 36 (1998), 121-126
Konferencje organizowane:
2.
Deep Learning Workshops, Kraków, 2018-02-20, 2018-02-23
1.
Theoretical Foundations of Machine Learning (TFML 2019) , Kraków, 2019-02-11, 2019-02-15
Doktoranci (po 27 października 2003 roku)
| Doktorant | Otwarcie | Zakonczenie |
|---|---|---|
| Krzysztof Misztal | 2011-05-26 | 2015-04-30 |
| Jakub Bielawski | 2010-06-24 | 2013-04-25 |
| Przemysław Spurek | 2012-05-31 | 2014-06-26 |
| Łukasz Struski | 2012-05-31 | 2014-01-30 |
| Łukasz Struski | 2013-03-28 | 2014-01-30 |
| Marek Śmieja | 2013-06-27 | 2015-01-29 |
| Tomasz Kulaga | 2009-06-25 | 2012-10-25 |
| Wojciech Czarnecki | 2014-06-26 | 2015-12-17 |
| Stanisław Jastrzębski | 2017-06-29 | 2019-03-28 |
| Andrzej Bedychaj | 2020-09-24 | |
| Agnieszka Wojtuch | 2018-09-27 | 2024-12-19 |
| Magdalena Wiercioch | 2016-06-30 | 2021-09-23 |
| Maciej Wołczyk | 2023-06-06 | 2024-04-25 |
| Dawid Rymarczyk | 2023-06-06 | 2024-04-25 |
| Magdalena Wiercioch | 2021-10-11 | 2023-12-14 |
| Adriana Borowa | 2024-09-26 |
Recenzje (po 27 października 2003 roku)
| Recenzowany | Jednostka | Treść recenzji |
|---|---|---|
| Doktorat: Natalia Żelazna | Katedra Matematyki Obliczeniowej | |
| Doktorat: Krzysztof Wesołowski | Katedra Teorii Aproksymacji |
Granty (realizowane po maju 2009 roku)
| Tytuł | Rola | Rozpoczęcie | Zakończenie |
|---|---|---|---|
| Meta-uczenie w głębokich sieciach neuronowych | Kierownik | 2024-01-29 | 2028-01-28 |
| Głębokie samoorganizujące się grafy neuronowe | Kierownik | 2022-02-04 | 2025-07-03 |
| Sztuczne sieci neuronowe inspirowane biologicznie | Kierownik | 2019-09-01 | 2023-11-29 |
| Efektywne metody uczenia nienadzorowanego z zastosowaniami w głębokim nauczaniu | Kierownik | 2018-02-09 | 2021-02-08 |
| Teoria analizy niekompletnych danych | Kierownik | 2016-07-13 | 2019-10-12 |
| Paradygmat minimalizacji pamięci w klastrowaniu | Kierownik | 2015-01-21 | 2017-08-26 |
| Uogólnienie entropii i wymiaru entropijnego oraz ich zastosowania | Kierownik | 2011-12-08 | 2014-12-07 |