2026-06-01T15:40:41Zhttps://riuma.uma.es/rest/oai/requestoai:riuma.uma.es:10630/402472026-02-03T11:18:53Zcom_10630_2254col_10630_37953
RIUMA. Repositorio Institucional de la Universidad de Málaga
author
Perfilieva, Irina
author
Madrid-Labrador, Nicolás Miguel
author
Ojeda-Aciego, Manuel
author
Artiemjew, Piotr
author
Niemczynowicz, Agnieszka
2025-10-15T10:54:41Z
2025-10-15T10:54:41Z
2025-01-02
Irina Perfilieva, Nicolás Madrid, Manuel Ojeda-Aciego, Piotr Artiemjew, Agnieszka Niemczynowicz: A critical analysis of the theoretical framework of the Extreme Learning Machine. Neurocomputing 621: 129298 (2025)
https://hdl.handle.net/10630/40247
10.1016/j.neucom.2024.129298
Despite several successful applications of the Extreme Learning Machine (ELM) as a new neural network training method that combines random selection with deterministic computation, we show that some fundamental principles of ELM lack a rigorous mathematical basis. In particular, we refute the proofs of two fundamental claims and construct datasets that serve as counterexamples to the ELM algorithm. Finally, we provide alternative claims to the basic principles that justify the effectiveness of ELM in some theoretical cases.
eng
Aprendizaje automático (Inteligencia artificial)
Redes neuronales (Informática)
Matrices (Matemáticas)
A critical analysis of the theoretical framework of the Extreme Learning Machine.
journal article
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URL
https://riuma.uma.es/bitstreams/da23ee50-4fdb-47a6-853e-48c8e12d13dc/download
File
MD5
b4ee8729a3423fa8c02e15c3dccedc78
3489462
application/pdf
NEUCOM-D-24-02193 copia.pdf