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Multi-Energy Load Prediction Method for Integrated Energy System Based on Fennec Fox Optimization Algorithm and Hybrid Kernel Extreme Learning Machine. [PDF]

Entropy (Basel)
Shen Y, Li D, Wang W.
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Extreme ensemble of extreme learning machines

Statistical Analysis and Data Mining: The ASA Data Science Journal, 2020
AbstractExtreme learning machine (ELM) has attracted attentions in pattern classification problems due to its preferences in low computations and high generalization. To overcome its drawbacks, caused by the randomness of input weights and biases, the ensemble of ELMs was proposed.
Eghbal G. Mansoori, Massar Sara
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Stacked Extreme Learning Machines

IEEE Transactions on Cybernetics, 2015
Extreme learning machine (ELM) has recently attracted many researchers' interest due to its very fast learning speed, good generalization ability, and ease of implementation. It provides a unified solution that can be used directly to solve regression, binary, and multiclass classification problems.
Hongming, Zhou, Guang-Bin, Huang, Zhiping, Lin, Han, Wang, Yeng Chai, Soh   +4 more
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BELM: Bayesian Extreme Learning Machine

IEEE Transactions on Neural Networks, 2011
The theory of extreme learning machine (ELM) has become very popular on the last few years. ELM is a new approach for learning the parameters of the hidden layers of a multilayer neural network (as the multilayer perceptron or the radial basis function neural network).
Emilio, Soria-Olivas, Juan, Gómez-Sanchis, José D, Martín, Joan, Vila-Francés, Marcelino, Martínez, José R, Magdalena, Antonio J, Serrano   +6 more
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Extreme Learning Machines [Trends & Controversies]

IEEE Intelligent Systems, 2013
This special issue includes eight original works that detail the further developments of ELMs in theories, applications, and hardware implementation. In "Representational Learning with ELMs for Big Data," Liyanaarachchi Lekamalage Chamara Kasun, Hongming Zhou, Guang-Bin Huang, and Chi Man Vong propose using the ELM as an auto-encoder for learning ...
Cambria, Erik, Huang, Guang Bin, Kasun, Liyanaarachchi Lekamalage Chamara, Zhou, Hongming, Vong, Chi Man, Lin, Jiarun, Yin, Jianping, Cai, Zhiping, Liu, Qiang, Li, Kuan, Leung, Victor C. M., Feng, Liang, Ong, Yew Soon, Lim, Meng Hiot, Akusok, Anton, Lendasse, Amaury, Corona, Francesco, Nian, Rui, Miche, Yoan, GASTALDO, PAOLO, ZUNINO, RODOLFO, DECHERCHI, SERGIO, Yang, Xuefeng, Mao, Kezhi, Oh, Beom Seok, Jeon, Jehyoung, Toh, Kar Ann, Teoh, Andrew Beng Jin, Kim, Jaihie, Yu, Hanchao, Chen, Yiqiang, Liu, Junfa   +31 more
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Robust extreme learning machine

Neurocomputing, 2013
The output weights computing of extreme learning machine (ELM) encounters two problems, the computational and outlier robustness problems. The computational problem occurs when the hidden layer output matrix is a not full column rank matrix or an ill-conditioned matrix because of randomly generated input weights and biases. An existing solution to this
Punyaphol Horata, Sirapat Chiewchanwattana, Khamron Sunat   +2 more
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Evolutionary extreme learning machine

Pattern Recognition, 2005
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zhu, Qin-Yu, Qin, A. K., Suganthan, P. N., Huang, Guang-Bin   +3 more
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Ordinal extreme learning machine

Neurocomputing, 2010
Recently, a new fast learning algorithm called Extreme Learning Machine (ELM) has been developed for Single-Hidden Layer Feedforward Networks (SLFNs) in G.-B. Huang, Q.-Y. Zhu and C.-K. Siew ''[Extreme learning machine: theory and applications,'' Neurocomputing 70 (2006) 489-501].
Wan-Yu Deng, Qing-Hua Zheng, Shiguo Lian, Lin Chen, Xin Wang   +4 more
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Extreme Learning Machines

2018
<p>Extreme Learning Machine (ELM) is a recently discovered way of training Single Layer Feed-forward Neural Networks with an explicitly given solution, which exists because the input weights and biases are generated randomly and never change. The method in general achieves performance comparable to Error Back-Propagation, but the training time is
Anton Akusok, Amaury Lendasse, Stephen Baek, Andrew Kusiak, Gregory R. Carmichael, Yong Chen, Ching-Long Lin   +6 more
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Regularized Extreme Learning Machine

2009 IEEE Symposium on Computational Intelligence and Data Mining, 2009
Extreme Learning Machine proposed by Huang G-B has attracted many attentions for its extremely fast training speed and good generalization performance. But it still can be considered as empirical risk minimization theme and tends to generate over-fitting model.
Wanyu Deng, Qinghua Zheng, Lin Chen
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