Ιδρυματικό Αποθετήριο
Πολυτεχνείο Κρήτης
Πολυτεχνείο Κρήτης
EN
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| URI: | http://purl.tuc.gr/dl/dias/6CA6D363-514F-49C7-AAE1-B15FE232BD4A | ||
| Έτος | 2017 | ||
| Τύπος | Πλήρης Δημοσίευση σε Συνέδριο | ||
| Άδεια Χρήσης |
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| Βιβλιογραφική Αναφορά | A. P. Liavas, G. Kostoulas, G. Lourakis, K. Huang and N. D. Sidiropoulos, "Nesterov-based parallel algorithm for large-scale nonnegative tensor factorization," in IEEE International Conference on Acoustics, Speech, and Signal Processing, 2017, pp. 5895-5899. doi: 10.1109/ICASSP.2017.7953287 https://doi.org/10.1109/ICASSP.2017.7953287 | ||
| Εμφανίζεται στις Συλλογές |
We consider the problem of nonnegative tensor factorization. Our aim is to derive an efficient algorithm that is also suitable for parallel implementation. We adopt the alternating optimization (AO) framework and solve each matrix nonnegative least-squares problem via a Nesterov-type algorithm for strongly convex problems. We describe a parallel implementation of the algorithm and measure the speedup attained by itsMessage Passing Interface implementation on a parallel computing environment. It turns out that the attained speedup is significant, rendering our algorithm a competitive candidate for the solution of very large-scale dense nonnegative tensor factorization problems.
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