Το έργο με τίτλο Alternating optimization for tensor factorization with orthogonality constraints: Algorithm and parallel implementation από τον/τους δημιουργό/ούς Karakasis Paris, Liavas Athanasios διατίθεται με την άδεια Creative Commons Αναφορά Δημιουργού 4.0 Διεθνές
Βιβλιογραφική Αναφορά
P. A. Karakasis and A. P. Liavas, "Alternating optimization for tensor factorization with orthogonality constraints: algorithm and parallel implementation," in 16th International Conference on High Performance Computing and Simulation, 2018, pp. 439-444. doi: 10.1109/HPCS.2018.00076
https://doi.org/10.1109/HPCS.2018.00076
We consider the problem of tensor factorization in the cases where one of the factors is constrained to have orthonormal columns. We adopt the alternating optimization framework and derive an efficient algorithm that is also suitable for parallel implementation. We describe in detail a distributed memory implementation of the algorithm on a three-dimensional processor grid. The speedup attained by a message-passing implementation of the algorithm is significant, indicating that it is a competitive candidate for the solution of very large tensor factorization problems with orthogonality constraints.