Acceleration and compression of deep neural networks using low-rank approximation methods
2023/49/N/ST6/02697
Keywords
Descriptors
- ST6_07: Sztuczna inteligencja, systemy inteligentne i wieloagentowe
- ST6_11: Uczenie maszynowe, statystyczne przetwarzanie danych i zastosowania w przetwarzaniu sygnałów (np. mowy, obrazów, filmów)
- ST6_12: Obliczenia naukowe, narzędzia modelowania i symulacji
Panel
ST6 – Computer science and informatics: informatics and information systems, computer science, scientific computing, intelligent systems
Host institution
Politechnika Wrocławska
Voivodeship: dolnośląskie
Principal investigator (from the host institution)
Number of co-investigators in the project: 2
Call
PRELUDIUM 22 – announced on 2023-03-16
- Amount awarded
- 89 694 PLN
- Project start date
- 2024-01-29
- Project end date
- 2026-12-28
- Project duration
- 35 months (the same as in the proposal)
- Project status
- Pending project
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.
Information in the final report
Publication in academic press/journals (1)
-
Reduced storage direct tensor ring decomposition for convolutional neural networks compression
- Authors:
- Mateusz Gabor, Rafał Zdunek
- Academic press:
- Neural Networks (year: 2026, volume: 193, pages: 46037), Publisher: Elsevier
- Status:
- Published
- DOI:
- 10.1016/j.neunet.2025.107994 – link to the publication
Articles in post-conference publications (1)
-
Positive concave deep equilibrium models
- Authors:
- Mateusz Gabor, Tomasz Piotrowski, Renato L. G. Cavalcante
- Conference:
- Proceedings of the 41st International Conference on Machine Learning (year: 2024, volume: International Conference on Machine Learning, pages: 14365–14381), Publisher: Proceedings of Machine Learning Research
- Date:
- conference 21-27.07.2024
- Status:
- Published
- DOI:
- link to the publication