Ever-increasing size and complexity of data sets create challenges and potential tradeoffs of accuracy and speed in learning algorithms. This paper offers progress on both fronts. It presents a mechanism to train the unsupervised learning features learned from only one layer to improve performance in both speed and accuracy. The features are learned by an unsupervised feature learning (UFL) algorithm. Then, those features are trained by a fast radial basis function (RBF) extreme learning machine (ELM). By exploiting the massive parallel computing attribute of modern graphics processing unit, a customized compute unified device architecture (CUDA) kernel is developed to further speed up the computing of the RBF kernel in the ELM. Results tes...
Currently, Extreme Learning Machine (ELM) is one of the research trends in the machine learning fiel...
AbstractThe emergence of the big data problem has pushed the machine learning research community to ...
The paper addresses the role of randomization in the training process of a learning machine, and ana...
Extreme learning machines (ELMs) have gained acceptance owing to their high efficiency and outstandi...
Extreme Learning Machine (ELM) as a type of generalized single-hidden layer feed-forward networks (S...
Neural Networks (NN) map input data to desired output data in image processing, time series predicti...
Extreme learning machine (ELM) has been developed for single hidden layer feedforward neural network...
Extreme Learning Machine (ELM) as a type of generalized single-hidden layer feed-forward networks (S...
Classification is one of the most essential tasks in machine learning which could be applied to many...
Today, we are living in a data-exploding era, in which the volume of data is expanding in an unbelie...
Extreme learning machine (ELM) is a new novel learning algorithm for generalized single-hidden layer...
The availability of compact fast circuitry for the support of artificial neural systems is a long-st...
Artificial neural network, or commonly referred to as ''neural network'', is a successful example of...
This thesis introduces novel fast learning algorithms for neural networks namely extreme learning ma...
The machine learning techniques have been extensively studied in the past few decades. One of the mo...
Currently, Extreme Learning Machine (ELM) is one of the research trends in the machine learning fiel...
AbstractThe emergence of the big data problem has pushed the machine learning research community to ...
The paper addresses the role of randomization in the training process of a learning machine, and ana...
Extreme learning machines (ELMs) have gained acceptance owing to their high efficiency and outstandi...
Extreme Learning Machine (ELM) as a type of generalized single-hidden layer feed-forward networks (S...
Neural Networks (NN) map input data to desired output data in image processing, time series predicti...
Extreme learning machine (ELM) has been developed for single hidden layer feedforward neural network...
Extreme Learning Machine (ELM) as a type of generalized single-hidden layer feed-forward networks (S...
Classification is one of the most essential tasks in machine learning which could be applied to many...
Today, we are living in a data-exploding era, in which the volume of data is expanding in an unbelie...
Extreme learning machine (ELM) is a new novel learning algorithm for generalized single-hidden layer...
The availability of compact fast circuitry for the support of artificial neural systems is a long-st...
Artificial neural network, or commonly referred to as ''neural network'', is a successful example of...
This thesis introduces novel fast learning algorithms for neural networks namely extreme learning ma...
The machine learning techniques have been extensively studied in the past few decades. One of the mo...
Currently, Extreme Learning Machine (ELM) is one of the research trends in the machine learning fiel...
AbstractThe emergence of the big data problem has pushed the machine learning research community to ...
The paper addresses the role of randomization in the training process of a learning machine, and ana...