Extreme learning machine (ELM) has gained increasing interest from various research fields
recently. In this review, we aim to report the current state of the theoretical research and …

Feedforward neural networks (FFNN) have been utilised for various research in machine
learning and they have gained a significantly wide acceptance. However, it was recently …

Extreme learning machines (ELMs) basically give answers to two fundamental learning
problems:(1) Can fundamentals of learning (ie, feature learning, clustering, regression and …

The emergent machine learning technique—extreme learning machines (ELMs)—has
become a hot area of research over the past years, which is attributed to the growing …

Automatic age and gender classification has been widely used in a large amount of
applications, particularly in human-computer interaction, biometrics, visual surveillance …

Extreme learning machine (ELM), which was originally proposed for" generalized" single-
hidden layer feedforward neural networks (SLFNs), provides efficient unified learning …

This paper addresses an important issue known as sensor drift, which exhibits a nonlinear
dynamic property in electronic nose (E-nose), from the viewpoint of machine learning …

Recent research has shown the speed advantage of extreme learning machine (ELM) and
the accuracy advantage of sparse representation classification (SRC) in the area of image …

As data sets become larger and more complicated, an extreme learning machine (ELM) that
runs in a traditional serial environment cannot realize its ability to be fast and effective …

With the direct input–output connections, a random vector functional link (RVFL) network is a
simple and effective learning algorithm for single-hidden layer feedforward neural networks …