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...
- 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