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Artificial Intelligence Review

Erschienen in:

01.06.2015

Extreme learning machine: algorithm, theory and applications

verfasst von: Shifei Ding, Han Zhao, Yanan Zhang, Xinzheng Xu, Ru Nie

Erschienen in: Artificial Intelligence Review | Ausgabe 1/2015

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Extreme learning machine (ELM) is a new learning algorithm for the single hidden layer feedforward neural networks. Compared with the conventional neural network learning algorithm it overcomes the slow training speed and over-fitting problems. ELM is based on empirical risk minimization theory and its learning process needs only a single iteration. The algorithm avoids multiple iterations and local minimization. It has been used in various fields and applications because of better generalization ability, robustness, and controllability and fast learning rate. In this paper, we make a review of ELM latest research progress about the algorithms, theory and applications. It first analyzes the theory and the algorithm ideas of ELM, then tracking describes the latest progress of ELM in recent years, including the model and specific applications of ELM, finally points out the research and development prospects of ELM in the future.

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Titel: Extreme learning machine: algorithm, theory and applications
verfasst von: Shifei Ding
Han Zhao
Yanan Zhang
Xinzheng Xu
Ru Nie
Publikationsdatum: 01.06.2015
Verlag: Springer Netherlands
Erschienen in: Artificial Intelligence Review / Ausgabe 1/2015
Print ISSN: 0269-2821
Elektronische ISSN: 1573-7462
DOI: https://doi.org/10.1007/s10462-013-9405-z

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