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Technical University of Crete
Technical University of Crete
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| URI | http://purl.tuc.gr/dl/dias/8BB84BD1-7ED4-4E9E-9398-CB066FEEA045 | - |
| Identifier | https://doi.org/10.23919/EUSIPCO54536.2021.9616067 | - |
| Identifier | https://ieeexplore.ieee.org/document/9616067 | - |
| Language | en | - |
| Extent | 5 pages | en |
| Title | Accelerated stochastic gradient for nonnegative tensor completion and parallel implementation | en |
| Creator | Siaminou Ioanna | en |
| Creator | Σιαμινου Ιωαννα | el |
| Creator | Papagiannakos Ioannis-Marios | en |
| Creator | Παπαγιαννακος Ιωαννης-Μαριος | el |
| Creator | Kolomvakis Christos | en |
| Creator | Κολομβακης Χρηστος | el |
| Creator | Liavas Athanasios | en |
| Creator | Λιαβας Αθανασιος | el |
| Publisher | Institute of Electrical and Electronics Engineers | en |
| Content Summary | We consider the problem of nonnegative tensor completion. We adopt the alternating optimization framework and solve each nonnegative matrix completion problem via a stochastic variation of the accelerated gradient algorithm. We experimentally test the effectiveness and the efficiency of our algorithm using both real-world and synthetic data. We develop a shared-memory implementation of our algorithm using the multithreaded API OpenMP, which attains significant speedup. We believe that our approach is a very competitive candidate for the solution of very large nonnegative tensor completion problems. | en |
| Type of Item | Δημοσίευση σε Συνέδριο | el |
| Type of Item | Conference Publication | en |
| License | http://creativecommons.org/licenses/by/4.0/ | en |
| Date of Item | 2023-05-26 | - |
| Date of Publication | 2021 | - |
| Subject | Tensors | en |
| Subject | Stochastic gradient | en |
| Subject | Nonnegative tensor completion | en |
| Subject | Optimal first-order optimization algorithms | en |
| Subject | Parallel algorithms | en |
| Subject | OpenMP | en |
| Bibliographic Citation | I. Siaminou, I. M. Papagiannakos, C. Kolomvakis and A. P. Liavas, "Accelerated stochastic gradient for nonnegative tensor completion and parallel implementation," in 2021 29th European Signal Processing Conference (EUSIPCO), Dublin, Ireland, 2021, pp. 1790-1794, doi: 10.23919/EUSIPCO54536.2021.9616067. | en |
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