New ALS Methods With Extrapolating Search Directions and Optimal Step Size for Complex-Valued Tensor Decompositions

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A literature survey of low‐rank tensor approximation techniques (2013, neutral): “…efﬁciency and robustness of gradient-based and Newton-like methods [2,72,74,140,223,224], modifying and improving ALS (alternating least squares) [41, 57, 58, 90, 225], studying the convergence of ALS [51, 194, 253] and reducing the cost of the unfolding operations required during the…”
CANDECOMP/PARAFAC Decomposition of High-Order Tensors Through Tensor Reshaping (2012, methodology): “For example, there are numerous algor ithms for CPD including the alternating least squares (ALS) algorithm [1], [2] with line search extrapola tion methods [1], [5], [23]–[25], rotation [26] and compression [27], or all-at-once algorithms such as the OPT algorithm [28], the conjugate gradient algor”