prof. dr hab. Jacek Tabor

Jednostki:

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

HabilitacjaOtwarcie: 2006-04-27, Zamknięcie: 2008-06-05

ProfesuraOtwarcie: 2013-05-23, Zamknięcie: 2015-07-17

Publikacje:

98.
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),
95.
Flow-based SVDD for anomaly detection, INTERNATIONAL CONFERENCE ON MACHINE LEARNING (WORKSHOP TRACK) (2020),
94.
Przemysław Spurek, Jacek Tabor, Tomasz Trzcinski, Sebastian Winczowski, Maciej Zamorski
Hypernetwork approach to generating point clouds, INTERNATIONAL CONFERENCE ON MACHINE LEARNING [ICML] (2020),
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.
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
77.
Processing of missing data by neural networks, ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS vol. 31 (2018), 2719--2729
69.
R Package CEC , NEUROCOMPUTING vol. 237 (2017), 410–413
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
63.
Online Extreme Entropy Machines for Streams Classification and Active Learning, ADVANCES IN INTELLIGENT SYSTEMS AND COMPUTING vol. 403 (2016), 371-381
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
56.
Spherical Wards clustering and generalized Voronoi diagrams, PROCEEDING OF IEEE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND ADVANCED ANALYTICS vol. 36678 (2015), 10
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
46.
Andrzej Bojarski, Marek Śmieja, Jacek Tabor, Dawid Warszycki
44.
Renyi entropy dimension of the mixture of measures, PROCEEDINGS OF SCIENCE AND INFORMATION CONFERENCE (2014), 685-689
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
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.
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
28.
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
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.
Approximately Midconvex Functions vol. Springer Optimization and Its Applications (2012), "Functional Equations in Mathematical Analysis", Springer Verlag (połaczony z Kluwer Academic Publishing)
23.
22.
Anna Mureńko, Jacek Tabor, Józef Tabor
21.
Tomasz Kułaga, Jacek Tabor
19.
Jacek Tabor, Józef Tabor, Marek Żołdak
18.
Adam Najdecki, Jacek Tabor, Józef Tabor
17.
Jacek Tabor, Józef Tabor, Marek Żołdak
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
13.
12.
Jacek Tabor, Józef Tabor
11.
Jacek Tabor, Józef Tabor
5.
Bogdan Batko, Zygfryd Kominek, Jacek Tabor
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

Doktoranci (po 27 października 2003 roku)

DoktorantOtwarcieZakonczenie
Krzysztof Misztal2011-05-262015-04-30
Marek Śmieja2013-06-272015-01-29
Przemysław Spurek2012-05-312014-06-26
Łukasz Struski2012-05-312014-01-30
Łukasz Struski2013-03-282014-01-30
Jakub Bielawski2010-06-242013-04-25
Tomasz Kulaga2009-06-252012-10-25
Wojciech Czarnecki2014-06-262015-12-17
Stanisław Jastrzębski2017-06-292019-03-28
Magdalena Wiercioch2016-06-30 
Agnieszka Pocha2018-09-27 

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
Sztuczne sieci neuronowe inspirowane biologicznieKierownik2019-09-012023-08-31
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