Extreme learning machine (ELM) has been developed for single hidden layer feedforward
neural networks (SLFNs). In ELM algorithm, the connections between the input layer and the …

The suicide of a person is a tragedy that deeply affects families, communities, and countries.
According to the standardized rate of suicides per number of inhabitants worldwide, in 2022 …

The potentially detrimental effects of cyberbullying have led to the development of numerous
automated, data-driven approaches, with emphasis on classification accuracy …

The extreme learning machine (ELM) has drawn insensitive research attentions due to its
effectiveness in solving many machine learning problems. However, the matrix inversion …

In this paper, we propose a novel extension of the extreme learning machine (ELM)
algorithm for single-hidden layer feedforward neural network training that is able to …

Along with the rapid development of intelligent mobile terminals, applications on landmark
recognition attract increasingly attentions by world wide researchers in the past several …

Unsupervised anomaly detection in time series remains challenging, due to the rare and
complex patterns of anomalous data. Previous change point detection methods based on …

Along with the rapid development of mobile terminal devices, landmark recognition
applications based on mobile devices have been widely researched in recent years. Due to …

Discriminative clustering is an unsupervised learning framework which introduces the
discriminative learning rule of supervised classification into clustering. The underlying …

In this paper, we propose an approximation scheme of the Kernel Extreme Learning
Machine algorithm for Single-hidden Layer Feedforward Neural network training that can be …