We consider the use of extreme learning machines (ELM) for computational partial differential equations (PDE). In ELM hidden-layer coefficients in neural network are assigned to random values generated on $[-R_m,R_m]$ and fixed, where $R_m$ is a user-provided constant, output-layer trained by linear or nonlinear least squares computation. present method computing optimal value based evolution a...

Extreme learning machine (ELM) is known as a kind of single-hidden layer feedforward network (SLFN), and has obtained considerable attention within the machine learning community and achieved various real-world applications. It has advantages such as good generalization performance, fast learning speed, and low computational cost. However, the ELM might have problems in the classification of im...

In Artificial Intelligence classification is a process of identifying classes of a different entities on the basis information provided from the dataset. Extreme Learning Machine (ELM) is one of the efficient classifiers. ELM is formed by interconnected layers. Each layer has many nodes (neurons). The input layer communicates with hidden layer with random weight and produces output layer with t...

Extreme learning machines (ELMs) has been theoretically and experimentally proved to achieve promising performance at a fast speed for supervised classification tasks. However, it does not perform well on imbalanced binary tasks tends get biased toward the majority class. Besides, since large amount of training data with labels are always available in real world, there is an urgent demand devel...

The existing sparse representation-based visual trackers mostly suffer from both being time consuming and having poor robustness problems. To address these issues, a novel tracking method is presented via combining sparse representation and an emerging learning technique, namely extreme learning machine (ELM). Specifically, visual tracking can be divided into two consecutive processes. Firstly,...

Crowd density estimation in public areas with people gathering and waiting is the important content of intelligent crowd surveillance. A real-time and high accuracy algorithm is necessary to be inputted in the classification and regression of crowd density estimation to improve the speed and increase the efficiency. Extreme Learning Machine (ELM) is a neural network architecture in which hidden...

—Extreme learning machine (ELM) is an extremely fast learning method and has a powerful performance for pattern recognition tasks proven by enormous researches and engineers. However, its good generalization ability is built on large numbers of hidden neurons, which is not beneficial to real time response in the test process. In this paper, we proposed new ways, named " constrained extreme lear...