A Review on Large-Scale Data Processing with Parallel and Distributed Randomized Extreme Learning Machine Neural Networks

The randomization-based feedforward neural network has raised great interest in the scientific community due to its simplicity, training speed, and accuracy comparable to traditional learning algorithms. The basic algorithm consists of randomly determining the weights and biases of the hidden layer...

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Autores:
Gelvez-Almeida, Elkin
Mora, Marco
Barrientos, Ricardo
Hernández García, Ruber
Vilches, Karina
Vera, Miguel
Tipo de recurso:
Fecha de publicación:
2024
Institución:
Universidad Simón Bolívar
Repositorio:
Repositorio Digital USB
Idioma:
eng
OAI Identifier:
oai:bonga.unisimon.edu.co:20.500.12442/16208
Acceso en línea:
https://hdl.handle.net/20.500.12442/16208
https://doi.org/10.3390/mca29030040
Palabra clave:
Randomization-Based Feedforward Neural Network
Extreme Learning Machine
Moore–Penrose generalized inverse matrix
Parallel and distributed computing
Rights
openAccess
License
http://purl.org/coar/access_right/c_abf2