In the present work, multiple convolutional and pooling layers of Deep Learning Networks (DLN) will extract efficiently the high level features of the face database. These features are given to the Kernel Extreme Learning Machine (KELM) classifier whose parameters are optimized using Particle Swarm ...
Based on this, this paper proposes a multi-label learning algorithm with kernel extreme learning machine autoencoder. Firstly, the label space is reconstructed by using the non-equilibrium labels completion method in the label space. Then, the non-equilibrium labels space information is added to ...
Deep kernel extreme learning machine classifier based on the improved sparrow search algorithm In the classification problem, deep kernel extreme learning machine (DKELM) has the characteristics of efficient processing and superior performance, but i... G Zhao,Y Lei - 《Journal of China Universities...
The MRKELM model is developed on the basis of the multiple kernel leaning method and the reduced kernel extreme learning machine method. In the presented MRKELM, the kernel function are not fixed anymore, multiple kernels are adaptively trained as a hybrid kernel and the optimal kernel ...
Incremental extreme learning machine (IELM)Multiple kernel learning (MKL)Non-iterative learningRobo-advisorsRobo-advisors are a class of robots based on the financial needs of investors, through the algorithm and products to complete the previous financial advisory services provided by human intervention....
Optimized feature fusion-based modified cascaded kernel extreme learning machine for heart disease prediction in E-healthcare Browse Login|Register Home All Journals Engineering & Technology Computer Methods in Biomechanics and Biomedical Engineering
Keywords Classification Kernel Learning Semi-supervised Learning Multi-Kernel Learning Extreme Learning Machine View PDFReferences 1 Guang-Bin Huang, Qin-Yu Zhu and Chee-Kheong Siew, “Extreme Learning Machine: A New Learning Scheme of Feedforward Neural Networks”, IEEE 2004. Google Scholar 2 Akusok...
In this paper, we relax the prediction error to any distribution for the kernel extreme learning machine. The method is called the error-distribution-free kernel extreme learning machine (ɛɛDFKELM). In this way, we can obtain the mixture correntropy criterion (MCC) by Xing and Wang, ...
This paper introduces a Kernel Extreme Learning Machine (KELM) for SFP. To optimize the hyperparameters of the classifier and also enhance the classification accuracy, the War Strategy Optimization (WSO) algorithm is employed here. The experimental evaluations are conducted using different baseline ...
we design a new LLP method LLP-KELM, which links inverse classifier calibration [6,24,27] to kernel extreme learning machine (KELM) [13]. It overcomes the disadvantage that the node number of hidden layer need to be manually set. Moreover, the performance has been significantly improved than...