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MEMS Gyroscope Temperature Compensation Based on Improved Complete Ensemble Empirical Mode Decomposition and Optimized Extreme Learning Machine. [PDF]

Micromachines (Basel)
Zhang Z, Zhang J, Zhu X, Ren Y, Yu J, Cao H.   +5 more
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Digital innovations in historical climatology: Classifying weather and climatic extremes and their impacts on societies using machine learning on written documents

Michael Kahle, Rüdiger Glaser
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Large scale wireless indoor localization by clustering and Extreme Learning Machine

, 2012
Wendong Xiao, Peidong Liu, Wee-Seng Soh, Guang-Bin Huang   +3 more
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Extreme Learning Machine for Efficient Multiclass Skin Lesion Classification

Mariano Rivera, Claudia Vidales-Basurto
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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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