Parallel Algorithms for Constrained Tensor Factorization via Alternating Direction Method of Multipliers

Tensor factorization has proven useful in a wide range of applications, from sensor array processing to communications, speech and audio signal processing, and machine learning. With few recent exceptions, all tensor factorization algorithms were originally developed for centralized, in-memory compu...

Celý popis

Podrobná bibliografie

Vydáno v:	IEEE transactions on signal processing Ročník 63; číslo 20; s. 5450 - 5463
Hlavní autoři:	Liavas, Athanasios P., Sidiropoulos, Nicholas D.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York IEEE 15.10.2015 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Algorithms Analytical models Computer architecture Matrices Optimization PARAFAC model parallel algorithms Signal processing algorithms Sparse matrices Tensile stress Tensor decomposition
ISSN:	1053-587X, 1941-0476
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!