Feb 15, 2013 · This paper presents an evolutionary approach for constituting extreme learning machine (ELM) ensembles. Our proposed algorithm employs the model diversity as ...
Feb 15, 2013 · This paper presents an evolutionary approach for constituting extreme learning machine (ELM) ensembles. Our proposed algorithm employs the model ...
Using extreme learning machines, a two-stage evolutionary algorithm is proposed for feature selection and setting hidden layer size, as well as to select ...
The ensemble is constructed by training a randomly chosen ELM classifier on a subset of training data selected through random resampling. The proposed AELM- ...
In this paper, we propose a silicon implementation of extreme learning machines (ELM) using spiking neural circuits. The major components of a silicon spiking ...
Oct 22, 2024 · Ensemble learning aims to improve the generalization power and the reliability of learner models through sampling and optimization ...
Abstract — Extreme Learning Machine (ELM) is a single-hidden-layer feedforward neural network which has been applied into many real world pattern ...
Genetic ensemble of extreme learning machine | Neurocomputing
dl.acm.org › doi › j.neucom.2013.09.042
Alhamdoosh, Evolutionary extreme learning machine ensembles with size control, Neurocomputing, Vol. 102, 2013, pp. 98-108. Digital Library · Google Scholar.
Aug 14, 2014 · Voting-based extreme learning machine (V-ELM) was proposed to improve learning efficiency where majority voting was employed.
Dec 2, 2023 · In this paper, we address the problem of reducing the computational cost of the model used for RUL prediction by employing the extreme learning ...
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