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:
184.
InTAct: Interval-based Task Activation Consolidation for Continual Learning, Advances in Neural Information Processing Systems [NeurIPS](MAIN), (2027),
183.
ProDG: Prototypes for Data-Free Generative Post-Hoc Explainability, Advances in Neural Information Processing Systems [NeurIPS](MAIN), (2027),
182.
GaMeS: Mesh-based adapting and modification of Gaussian Splatting, Pattern Recognition vol. 181 (2027), 114561
181.
Szymon Płotka, Gizem Mert, Pedro Bassi, Wenxuan Li, Zongwei Zhou, Anna Marcinkiewicz, Wiktoria Romańczyk, Jarosław Ćwikła, Łukasz Struski, Ewa Szczurek, Jacek Tabor, Arkadiusz Sitek
Anatomy-Activated Mixture-of-Experts for 3D Medical Vision-Language Pre-training, Advances in Neural Information Processing Systems [NeurIPS], (2026),
180.
LAPLEX: The FFT of Learnable Laplace Kernels, Advances in Neural Information Processing Systems [NeurIPS], (2026),
179.
178.
Krzysztof Byrski, Marcin Mazur, Jacek Tabor, Tadeusz Dziarmaga, Marcin Kądziołka, Dawid Baran, Przemysław Spurek
RaySplats: Ray Tracing Based Gaussian Splatting, International Conference on Neural Information Processing [ICONIP], (2026), accepted
177.
Mikołaj Zasada, Łukasz Struski, Jacek Tabor, Marcin Kurdziel
SoftMoE: Soft Differentiable Routing for Mixture-of-Experts in LLMs, International Conference on Machine Learning [ICML], (2026),
176.
Georgii Stanishevskii, Jakub Steczkiewicz, Tomasz Szczepanik, Sławomir K. Tadeja, Przemysław Spurek, Jacek Tabor
Deepfake for the good: Generating avatars through face-swapping with implicit deepfake generation, Asian Conference on Intelligent Information and Database Systems [ACIIDS], (2026), 151-165
175.
Alicja Polowczyk, Agnieszka Polowczyk, Dawid Malarz, Artur Kasymov, Jacek Tabor, Marcin Mazur, Przemysław Spurek
UnGuide: Learning to Forget with LoRA-Guided Diffusion Models, Conference in Uncertainty in Artificial Intelligence [UAI](MAIN) vol. 337 (2026), 5471--5503
174.
DAVE : Distribution-aware Attribution via ViT Gradient Decomposition, International Conference on Machine Learning [ICML], (2026),
173.
Piotr Borycki, Magdalena Trędowicz, Szymon Janusz, Jacek Tabor, Przemysław Spurek, Arkadiusz Lewicki, Łukasz Struski
EPIC: Explanation of Pretrained Image Classification Networks via Prototypes, National Conference of the American Association for Artificial Intelligence [AAAI](MAIN) vol. 40(21) (2026), 17366-17373
172.
Mateusz Pach, Przemysław Rola, Michał Znaleźniak, Patryk Kaszuba, Marcin Przewięźlikowski, Jacek Tabor, Marek Śmieja
171.
170.
ZEUS: Zero-shot Embeddings for Unsupervised Separation of Tabular Data, Advances in Neural Information Processing Systems [NeurIPS](MAIN) vol. Advances in Neural Information Processing Systems 38 (2026), 96173-96210
169.
Klaudia Bałazy, Julian McAuley, Jacek Tabor
A Deeper Look into the Limitations of Early-Exit Architectures for Single and Multi-label Classification, International Conference on Computational Science [ICCS], (2025), 179–193
168.
Klaudia Bałazy, Mohammadreza Banaei, Karl Aberer, Jacek Tabor
LoRA-XS: low-rank adaptation with extremely small number of parameters, European Conference on Artificial Intelligence [ECAI], (2025), 3194 - 3201
167.
Minimal Ranks, Maximum Confidence: Parameter-efficient Uncertainty Quantification for LoRA, Empirical Methods in Natural Language Processing [EMNLP](MAIN), (2025), 1260-1271
166.
Classifier-Free Guidance with Adaptive Scaling, European Conference on Artificial Intelligence [ECAI] vol. 413 (2025), 435 - 442
165.
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
164.
Piotr Gaiński, Michał Koziarski, Krzysztof Maziarz, Marvin Segler, Jacek Tabor, Marek Śmieja
Diverse and feasible retrosynthesis using gflownets, Information Sciences vol. 714 (2025), 122184
163.
PrAViC: Probabilistic Adaptation Framework for Real-Time Video Classification, European Conference on Artificial Intelligence [ECAI](MAIN) vol. 413: ECAI 2025 (2025), 411-418
162.
LapSum - One Method to Differentiate Them All: Ranking, Sorting and Top-k Selection, International Conference on Machine Learning [ICML], (2025),
161.
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 (2025), 0312038
160.
SEMU: Singular Value Decomposition for Efficient Machine Unlearning, International Conference on Machine Learning [ICML] vol. 267 Proceedings of Machine Learning (2025), 53843-53866
159.
Piotr Borycki, Kubacki Piotr, Marcin Przewięźlikowski, Jacek Tabor, Przemysław Spurek, Tomasz Kuśmierczyk
Hypernetwork Approach to Bayesian MAML (Student Abstract), National Conference of the American Association for Artificial Intelligence [AAAI] vol. 39 (2025), 29325-29327
158.
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
157.
CEC-MMR: Cross-Entropy Clustering Approach to Multi-Modal Regression, IEEE International Joint Conference on Neural Networks [IJCNN](MAIN), (2025), 1-7
156.
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
155.
VisTabNet: Adapting Vision Transformers for Tabular Data, SIAM International Conference on Data Mining [SDM], (2025), 497-506
154.
NegGS: Negative Gaussian Splatting, Information Sciences vol. 702 (2025), 121912
153.
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
152.
Gaussian Splatting with NeRF-based color and opacity, Computer Vision and Image Understanding vol. 251 (2025), 104237
151.
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
150.
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
149.
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
148.
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
147.
HyperMAML: Few-shot adaptation of deep models with hypernetworks, Neurocomputing vol. 598 (2024), 128-179
146.
NeRFlame: Flame-Based Conditioning of NeRF for 3D Face Rendering, International Conference on Computational Science [ICCS](MAIN) vol. 14832 (2024), 346--361
145.
Gaussian model for closed curves, Expert Systems with Applications vol. 249 part B (2024), 123615
144.
Bartosz Zieliński, Adriana Borowa, Dawid Rymarczyk, Marek Żyła, Marek Kańduła, Ana Sánchez-Fernández, Krzysztof Rataj, Łukasz Struski, Jacek Tabor
143.
142.
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
141.
Face Identity-Aware Disentanglement in StyleGAN, IEEE Workshop on Applications of Computer Vision [WACV], (2024), 5222-5231
140.
139.
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
138.
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
137.
ProPML: Probability Partial Multi-label Learning, IEEE International Conference on Data Science and Advanced Analytics [DSAA], (2023), 1-8
136.
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
135.
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
134.
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
133.
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
132.
Przemysław Spurek, Marcin Sendera, Marcin Przewięźlikowski, Jan Miksa, Mateusz Rajski, Konrad Karanowski, Maciej Zieba, Jacek Tabor
131.
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
130.
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
129.
Bounding Evidence and Estimating Log-Likelihood in VAE, International Conference on Artificial Intelligence and Statistics [AISTATS](MAIN) vol. 206 (2023), 5036-5051
128.
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
127.
ProtoSeg: Interpretable Semantic Segmentation with Prototypical Parts, IEEE Workshop on Applications of Computer Vision [WACV](MAIN) vol. 2023 (2023), 1481-1492
126.
SONGs: Self-Organizing Neural Graphs, IEEE Workshop on Applications of Computer Vision [WACV](MAIN), (2023), 3837-3846
125.
SLOVA: Uncertainty estimation using single label one-vs-all classifier, Applied Soft Computing Journal vol. 126 (2022), 109219
124.
123.
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
122.
Batch size reconstruction-distribution trade-off in kernel based generative autoencoders, IEEE International Conference on Image Processing [ICIP], (2022), 3728-3732
121.
Nonlinear Weighted Independent Component Analysis, International Conference on Information Processing and Management of Uncertainty [IPMU] vol. II (2022), 3–16
120.
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
119.
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
118.
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
117.
LocoGAN—Locally convolutional GAN, Computer Vision and Image Understanding vol. 221 (2022), 103462
116.
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
115.
Generative models with kernel distance in data space, Neurocomputing vol. 487 (2022), 119-129
114.
MisConv: Convolutional Neural Networks for Missing Data, IEEE Workshop on Applications of Computer Vision [WACV], (2022), 2060-2069
113.
Łukasz Struski, Jacek Tabor, Szymon Bobek, Sławomir K. Tadeja, Przemysław Stachura, Timoleon Kipourus, Grzegorz Nalepa, Per Ola Kristensson
112.
111.
Zięba Maciej , Przemysław Spurek, Jacek Tabor, Tomasz Trzciński
110.
Adversarial Examples Detection and Analysis with Layer-wise Autoencoders, International Conference on Tools with Artificial Intelligence [ICTAI], (2021), 1322-1326
109.
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
108.
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
107.
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
106.
Comparison of Atom Representations in Graph Neural Networks for Molecular Property Prediction, IEEE International Joint Conference on Neural Networks [IJCNN], (2021), 1-8
105.
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
104.
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
103.
SeGMA: Semi-Supervised Gaussian Mixture Autoencoder, IEEE Transactions on Neural Networks and Learning Systems vol. 32/9 (2021), 3930-3941
102.
Andrzej Bojarski, Stanisław Jastrzębski, Stefan Mordalski, Sabina Podlewska, Maciej Szymczak, Jacek Tabor, Agnieszka Wojtuch
101.
Fast and Stable Interval Bounds Propagation for Training Verifiably Robust Models, European Symposium on Artificial Neural Networks [ESANN], (2020), 6
100.
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
99.
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),
98.
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),
97.
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),
96.
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),
95.
Andrzej Bojarski, Stanisław Jastrzębski, Stefan Mordalski, Sabina Podlewska, Maciej Szymczak, Jacek Tabor, Agnieszka Wojtuch
94.
Cramer-Wold Auto-Encoder, Journal of Machine Learning Research vol. 21 (2020), 1-28
93.
Flow-based SVDD for anomaly detection, International Conference On Machine Learning (workshop Track) (2020),
92.
Pointed subspace approach to incomplete data, Journal of Classification vol. 37 (2020), 42-57
91.
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
90.
Andrzej Bojarski, Stanisław Jastrzębski, Damian Leśniak, Sabina Podlewska, Igor Sieradzki, Jacek Tabor
89.
Generalized RBF kernel for incomplete data, Knowledge-Based Systems vol. 173 (2019), 150-162
88.
87.
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
86.
Tomasz Danel, Stanisław Jastrzębski, Łukasz Maziarka, Sławomir Mucha, Krzysztof Rataj, Jacek Tabor
Molecule-Augmented Attention Transformer, Neural Information Processing Systems (workshop Track) (2019),
85.
Hypernetwork Functional Image Representation, Artificial Neural Networks and Machine Learning – Icann 2019: Workshop and Special Sessions (2019), 496-510
84.
83.
Projected memory clustering, Pattern Recognition Letters vol. 123 (2019), 9-15
82.
Online updating of active function cross-entropy clustering, Pattern Analysis and Applications vol. vol. 22 no. 4 (2019), 1409-1425
81.
SVM with a neutral class, Pattern Analysis and Applications vol. 22/2 (2019), 573-582
80.
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
79.
Łukasz Maziarka, Jacek Tabor, Bartosz Wójcik
LOSSGRAD: Automatic Learning Rate in Gradient Descent, Schedae Informaticae vol. 27 (2018), 47-57
78.
Image Stitching Based on Entropy Minimization, Schedae Informaticae vol. 27 (2018), 129-141
77.
Sliced generative models, Schedae Informaticae vol. 27 (2018), 69-79
76.
75.
Processing of missing data by neural networks, Advances in Neural Information Processing Systems vol. 31 (2018), 2719-2729
74.
Oleksandr Myronov, Marek Śmieja, Jacek Tabor
Semi-supervised discriminative clustering with graph regularization, Knowledge-Based Systems vol. 151 (2018), 24-36
73.
Lossy Compression Approach to Subspace Clustering, Information Sciences vol. 435 (2018), 161-183
72.
71.
Regression SVM for incomplete data, Schedae Informaticae vol. 26 (2017), 23-35
70.
ICA based on asymmetry, Pattern Recognition vol. 67 (2017), 230-244
69.
Active Function Cross-Entropy Clustering, Expert Systems with Applications vol. 72 (2017), 49–66
68.
R Package CEC , Neurocomputing vol. 237 (2017), 410–413
67.
66.
65.
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
64.
Maximum Likelihood Estimation and Optimal Coordinates, International Conference On Systems Science, 2016 vol. Springer (2016), 3-13
63.
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
62.
Online Extreme Entropy Machines for Streams Classification and Active Learning, Advances in Intelligent Systems and Computing vol. 403 (2016), 371-381
61.
60.
59.
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
58.
Jacek Chudziak, Jacek Tabor, Józef Tabor
Conditionally d-midconvex functions, Aequationes Mathematicae vol. 89 (2015), 981-990
57.
Cross-Entropy based image thresholding, Schedae Informaticae vol. 24 (2015), 21-29
56.
55.
Spherical Wards clustering and generalized Voronoi diagrams, Proceeding of Ieee International Conference On Data Science and Advanced Analytics vol. 36678 (2015), 10
54.
Subspace memory clustering, Schedae Informaticae vol. 24 (2015), 133-142
53.
Wojciech Czarnecki, Rafał Józefowicz, Jacek Tabor
52.
Przemysław Spurek, Jacek Tabor, Mateusz Wójcik
Cross-Entropy Clustering Approach to One-Class Classification, Lecture Notes in Computer Science vol. 9119 (2015), 481-490
51.
Entropy approximation in lossy source coding problem, Entropy vol. 17/5 (2015), 3400-3418
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 | 2025-09-18 |
| Łukasz Maziarka | 2023-03-30 | 2025-11-20 |
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 |