Neural Networks Regularization With Graph-Based Local Resampling

Neural Networks Regularization With Graph-Based Local Resampling

This paper presents the concept of Graph-based Local Resampling of perceptron-like neural networks with random projections (RN-ELM) which aims at regularization of the yielded model. The addition of synthetic noise to the learning set finds some similarity with data augmentation approaches that are...

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Bibliographic Details
Main Authors: Alex D. Assis, Luiz C. B. Torres, Lourenco R. G. Araujo, Vitor M. Hanriot, Antonio P. Braga
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Classifier
neural network
regularization
training with noise
Online Access:https://ieeexplore.ieee.org/document/9383228/

Internet

https://ieeexplore.ieee.org/document/9383228/

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