Projects funded by the NCN

Information on the principal investigator and host institution

Information of the project and the call

Keywords

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Development of Models and Methods for Incorporating Knowledge to Support Vector Machines

2015/17/D/ST6/04010

Keywords:

support vector machines differential equations prior knowledge

Descriptors:

  • ST6_11: Machine learning, statistical data processing and applications using signal processing (e.g. speech, image, video)
  • ST6_4: Formal methods, foundations of computer science, including theoretical computer science, quantum algorithms
  • ST6_6: Algorithms, parallel, distributed and network algorithms, algorithmic game theory

Panel:

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

Host institution :

Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie, Wydział Informatyki, Elektroniki i Telekomunikacji

woj. małopolskie

Other projects carried out by the institution 

Principal investigator (from the host institution):

dr Marcin Orchel 

Number of co-investigators in the project: 1

Call: SONATA 9 - announced on 2015-03-16

Amount awarded: 130 076 PLN

Project start date (Y-m-d): 2016-02-15

Project end date (Y-m-d): 2020-02-14

Project duration:: 48 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. Stacja robocza (8 000 PLN)

Information in the final report

  • Articles in post-conference publications (5)
  1. Clustering by support vector manifold learning
    Authors:
    Marcin Orchel
    Conference:
    2017 International Joint Conference on Neural Networks (IJCNN 2017) (rok: 2017, ), Wydawca: IEEE
    Data:
    konferencja 14-19 Maj 2017
    Status:
    Published
  2. Knowledge-Uncertainty Axiomatized Framework with Support Vector Machines for Sparse Hyperparameter Optimization
    Authors:
    Marcin Orchel
    Conference:
    The International Joint Conference on Neural Networks (IJCNN) 2018 (rok: 2018, ), Wydawca: IEEE
    Data:
    konferencja 8-13 lipiec 2018
    Status:
    Published
  3. Axiomatic Kernels on Graphs for Support Vector Machines
    Authors:
    Marcin Orchel, Johan A.K. Suykens
    Conference:
    2019 - 28th International Conference on Artificial Neural Networks (ICANN 2019) (rok: 2019, ), Wydawca: Springer
    Data:
    konferencja 17-19 wrzesień 2019
    Status:
    Published
  4. Fast Hyperparameter Tuning for Support Vector Machines with Stochastic Gradient Descent
    Authors:
    Marcin Orchel, Johan A. K. Suykens
    Conference:
    Machine Learning, Optimization, and Data Science - 6th International Conference, LOD 2020 (rok: 2020, ), Wydawca: Springer
    Data:
    konferencja 19-23 lipiec 2020
    Status:
    Published
  5. Improved update rule and sampling of stochastic gradient descent with extreme early stopping for support vector machines
    Authors:
    Marcin Orchel, Johan A.K. Suykens
    Conference:
    The 7th Annual Conference on machine Learning, Optimization and Data science (LOD 2021) , Wydawca: Springer
    Data:
    konferencja 4-8 październik 2021
    Status:
    Accepted for publication

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