A Parallel Computing Method for the Computation of the Moore–Penrose Generalized Inverse for Shared-Memory Architectures

The computation of the Moore–Penrose generalized inverse is a commonly used operation in various fields such as the training of neural networks based on random weights. Therefore, a fast computation of this inverse is important for problems where such neural networks provide a solution. However, due...

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Autores:
Gelvez-Almeida, Elkin
Barrientos, Ricardo
Vilches, Karina
Mora, Marco
Tipo de recurso:
Fecha de publicación:
2023
Institución:
Universidad Simón Bolívar
Repositorio:
Repositorio Digital USB
Idioma:
eng
OAI Identifier:
oai:bonga.unisimon.edu.co:20.500.12442/16177
Acceso en línea:
https://hdl.handle.net/20.500.12442/16177
https://doi.org/10.1109/ACCESS.2023.3338544
https://ieeexplore.ieee.org/document/10336814
Palabra clave:
High-performance computing
Moore–Penrose generalized inverse matrix
Neural networks with random weights
Parallel computing
Strassen algorithm
Rights
openAccess
License
Attribution-NonCommercial-NoDerivs 3.0 United States