An ATLD–ALS method for the trilinear decomposition of large third-order tensors

Simonacci, Violetta; Gallo, Michele

doi:10.1007/s00500-019-04320-9

Cited by 5 publications

(2 citation statements)

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“…To address this difficulty, we propose to fit the quadrilinear decomposition through an integrated optimizing design called QINT-2. This procedure is a two-stage scheme extending the INT-2 algorithm (Simonacci and Gallo 2020) to a four-way setting. By estimating parameters in two steps, first with AQLD and then with QALS in a PFS array formulation, QINT-2 derives desirable properties from both algorithms.…”

Section: Discussionmentioning

confidence: 99%

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On four-way CP model estimation efficiency

Simonacci

Gallo

2022

Comput Stat

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The latent structure of four-dimensional tensors can be investigated by means of the four-way CANDECOMP/PARAFAC model. This technique is seldom used because its estimating design is challenging from an algorithmic and interpretational standpoint. Parameter estimation with a least-squares approach can be computationally costly, especially under difficult conditions such as factor collinearity and model over-specification. In this work, we implement a 4th-order extension of the efficient trilinear procedure INT-2 to tackle estimating setbacks and test it in a simulation study.

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Section: Discussionmentioning

confidence: 99%

“…Noise percentages (NOISE) are expressed in terms of total tensor inertia. For a more detailed explanation of data generation please refer to the appendix in Simonacci and Gallo (2020) where similar parameters are described in a three-way setting.…”

Section: Simulation Designmentioning

confidence: 99%