Projects funded by the NCN

Information on the principal investigator and host institution

Information of the project and the call

Keywords

Equipment

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Efficient unsupervised learning with applications in deep learning

2017/25/B/ST6/01271

Keywords:

unsupervised learning probabilistic methods deep learning

Descriptors:

  • ST6_11: Machine learning, statistical data processing and applications using signal processing (e.g. speech, image, video)

Panel:

ST6 - Computer science and informatics: informatics and information systems, computer science, scientific computing, intelligent systems

Host institution :

Uniwersytet Jagielloński, Wydział Matematyki i Informatyki

woj. małopolskie

Other projects carried out by the institution 

Principal investigator (from the host institution):

prof. Jacek Tabor 

Number of co-investigators in the project: 8

Call: OPUS 13 - announced on 2017-03-15

Amount awarded: 573 200 PLN

Project start date (Y-m-d): 2018-02-09

Project end date (Y-m-d): 2021-02-08

Project duration:: 36 months (the same as in the proposal)

Project status: Project settled

Project description

Download the project description in a pdf file

Note - project descriptions were prepared by the authors of the applications themselves and placed in the system in an unchanged form.

Equipment purchased [PL]

  1. serwer obliczeniowy.
  2. stacja robocza (23 975 PLN)
  3. Klaster komputerowy (100 000 PLN)
  4. tablet (5 977 PLN)

Information in the final report

  • Publication in academic press/journals (7)
  • Articles in post-conference publications (12)
  1. A classification-based approach to semi-supervised clustering with pairwise constraints
    Authors:
    Marek Śmieja, Łukasz Struski, Mario A. T. Figueiredo
    Academic press:
    Neural Networks (rok: 2020, tom: 127, strony: 193-203), Wydawca: Elsevier
    Status:
    Published
    DOI:
    10.1016/j.neunet.2020.04.017 - link to the publication
  2. Online updating of active function cross-entropy clustering
    Authors:
    Przemysław Spurek, Jacek Tabor, Krzysztof Byrski
    Academic press:
    Pattern Analysis and Applications (rok: 2019, tom: 22, strony: 1409-1425), Wydawca: Springer
    Status:
    Published
    DOI:
    10.1007/s10044-018-0701-8 - link to the publication
  3. Fast independent component analysis algorithm with a simple closed-form solution.
    Authors:
    Przemysław Spurek, Jacek Tabor, Łukasz Struski, Marek Śmieja
    Academic press:
    Knowledge-Based Systems 161 (2018): 26-34. (rok: 2018, tom: 161, strony: 26-34), Wydawca: Elsevier
    Status:
    Published
    DOI:
    10.1016/j.knosys.2018.07.027 - link to the publication
  4. SeGMA: Semi-Supervised Gaussian Mixture Autoencoder
    Authors:
    Marek Śmieja, Maciej Wołczyk, Jacek Tabor, Bernhard C. Geiger
    Academic press:
    IEEE Transactions on Neural Networks and Learning Systems (rok: 2020, tom: -, strony: 45303), Wydawca: IEEE
    Status:
    Published
    DOI:
    10.1109/TNNLS.2020.3016221 - link to the publication
  5. Efficient mixture model for clustering of sparse high dimensional binary data
    Authors:
    Marek Śmieja, Krzysztof Hajto, Jacek Tabor
    Academic press:
    Data Mining and Knowledge Discovery (rok: 2019, tom: 33, strony: 1583--1624), Wydawca: Springer
    Status:
    Published
    DOI:
    10.1007/s10618-019-00635-1 - link to the publication
  6. OneFlow: One-class flow for anomaly detection based on a minimal volume region
    Authors:
    Łukasz Maziarka; Marek Śmieja; Marcin Sendera; Łukasz Struski; Jacek Tabor; Przemysław Spurek
    Academic press:
    IEEE Transactions on Pattern Analysis and Machine Intelligence (rok: 2021, ), Wydawca: IEEE Transactions on Pattern Analysis and Machine Intelligence
    Status:
    Accepted for publication
    DOI:
    10.1109/TPAMI.2021.3108223 - link to the publication
  7. Projected memory clustering
    Authors:
    Łukasz Struski, Przemysław Spurek, Jacek Tabor, Marek Śmieja
    Academic press:
    Pattern Recognition Letters (rok: 2019, tom: 123, strony: 45550), Wydawca: Elsevier
    Status:
    Published
    DOI:
    10.1016/j.patrec.2019.02.023 - link to the publication
  1. Fast and Stable Interval Bounds Propagation for Training Verifiably Robust Models
    Authors:
    Paweł Morawiecki, Przemysław Spurek, Marek Śmieja, Jacek Tabor
    Conference:
    European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2020) (rok: 2020, ), Wydawca: Louvain-la-Neuve : i6doc
    Data:
    konferencja 44106
    Status:
    Published
  2. Set Aggregation Network as a Trainable Pooling Layer
    Authors:
    Łukasz Maziarka, Marek Śmieja, Aleksandra Nowak, Jacek Tabor, Łukasz Struski, Przemysław Spurek
    Conference:
    ICONIP (rok: 2019, ), Wydawca: Springer International Publishing
    Data:
    konferencja 2019
    Status:
    Published
  3. Biologically-Inspired Spatial Neural Networks
    Authors:
    Maciej Wołczyk, Jacek Tabor, Marek Śmieja, Szymon Maszke
    Conference:
    NeurIPS workshop on Real Neurons & Hidden Units (NeuroAI 2019) (rok: 2019, ), Wydawca: NeurIPS 2019
    Data:
    konferencja 2019
    Status:
    Published
  4. Estimating conditional density of missing values using deep gaussian mixture model
    Authors:
    Marcin Przewięźlikowski, Marek Śmieja, Łukasz Struski
    Conference:
    Neural Information Processing. ICONIP 2020. Lecture Notes in Computer Science (rok: 2020, ), Wydawca: Springer, Cham
    Data:
    konferencja 44122
    Status:
    Published
  5. Flow-based SVDD for anomaly detection
    Authors:
    Marcin Sendera, Marek Śmieja, Łukasz Maziarka, Łukasz Struski, Przemysław Spurek, Jacek Tabor
    Conference:
    Invertible Neural Networks, NormalizingFlows, and Explicit Likelihood Models(ICML 2020) (rok: 2020, ), Wydawca: ICML
    Data:
    konferencja 44030
    Status:
    Published
  6. Iterative imputation of missing data using auto-encoder dynamics
    Authors:
    Marek Śmieja, Maciej Kołomycki, Łukasz Struski, Mateusz Juda, Mario A. T. Figueiredo
    Conference:
    Neural Information Processing. ICONIP 2020. Lecture Notes in Computer Science (rok: 2020, ), Wydawca: Springer, Cham
    Data:
    konferencja 44122
    Status:
    Published
  7. Processing of incomplete images by (graph) convolutional neural networks
    Authors:
    Tomasz Danel, Marek Śmieja, Łukasz Struski, Przemysław Spurek, Łukasz Maziarka
    Conference:
    Neural Information Processing. ICONIP 2020. Lecture Notes in Computer Science (rok: 2020, ), Wydawca: Springer, Cham
    Data:
    konferencja 44122
    Status:
    Published
  8. Spatial graph convolutional networks
    Authors:
    Tomasz Danel, Przemysław Spurek, Jacek Tabor, Marek Śmieja, Łukasz Struski, Agnieszka Słowik, Łukasz Maziarka
    Conference:
    Neural Information Processing. ICONIP 2020. Communications in Computer and Information Science (rok: 2020, ), Wydawca: Springer, Cham.
    Data:
    konferencja 44122
    Status:
    Published
  9. Finding the Optimal Network Depth in Classification Tasks
    Authors:
    Bartosz Wójcik, Maciej Wołczyk, Klaudia Bałazy, Jacek Tabor
    Conference:
    Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2020 (rok: 2020, ), Wydawca: Springer, Cham
    Data:
    konferencja 44088
    Status:
    Published
  10. Non-linear ICA based on Cramer-Wold metric
    Authors:
    Przemysław Spurek, Aleksandra Nowak, Jacek Tabor, Łukasz Maziarka, Stanisław Jastrzębski
    Conference:
    Neural Information Processing. ICONIP 2020. Lecture Notes in Computer Science (rok: 2020, ), Wydawca: Springer, Cham
    Data:
    konferencja 44122
    Status:
    Published
  11. Can autoencoders help with filling missing data?
    Authors:
    Marek Śmieja, Maciej Kołomycki, Łukasz Struski, Mateusz Juda, Mário A. T. Figueiredo
    Conference:
    ICLR 2020 Workshop on Integration of Deep Neural Models and Differential Equations (rok: 2020, ), Wydawca: ICLR
    Data:
    konferencja 43947
    Status:
    Published
  12. Molecule-Augmented Attention Transformer
    Authors:
    Łukasz Maziarka, Tomasz Danel, Sławomir Mucha, Krzysztof Rataj, Jacek Tabor, Stanisław Jastrzębski
    Conference:
    Second Workshop on Machine Learning and the Physical Sciences (NeurIPS 2019), Vancouver, Canada (rok: 2019, ), Wydawca: NeurIPS 2019
    Data:
    konferencja 2019
    Status:
    Published

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