Nov 4, 2021 · Our approach is based on stochastic gradient descent (SGD) algorithm which allows us to parallelize the learning process and it is very useful ...
A fast parallel tensor decomposition with optimal stochastic gradient ...
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Jun 23, 2023 · We propose a novel algorithm, FP-CPD, to parallelize the CANDECOMP/PARAFAC (CP) decomposition of a tensor . Our approach is based on stochastic ...
Jun 11, 2023 · Our approach is based on stochastic gradient descent (SGD) algorithm which allows us to parallelize the learning process, and it is very useful ...
Nov 4, 2021 · Stochastic Gradient Descent: an Application in Structural. Damage ... structural health scores to identify the damage severity in a one ...
Nov 4, 2021 · Our approach is based on stochastic gradient descent (SGD) algorithm which allows us to parallelize the learning process and it is very useful ...
A fast parallel tensor decomposition with optimal stochastic gradient descent: an application in structural damage identification.
A Fast Parallel Tensor Decomposition with Optimal Stochastic Gradient Descent: an Application in Structural Damage Identification · no code implementations ...
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A fast parallel tensor decomposition with optimal stochastic gradient descent: an application in structural damage identification. Int. J. Data Sci. Anal ...
A fast parallel tensor decomposition with optimal stochastic gradient descent: an application in structural damage identification ... Int. J. Data Sci. Anal. 2024.
This survey provides an overview of higher-order tensor decompositions, their applications, and available software. A tensor is a multidimensional or N-way ...