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A Fast Algorithm for Sparse Extreme Learning Machine

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Proceedings of ELM 2018 (ELM 2018)

Part of the book series: Proceedings in Adaptation, Learning and Optimization ((PALO,volume 11))

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Abstract

As a more compact network, sparse ELM is an alternative model of extreme learning machine (ELM) for classification, which requires less memory space and testing time than conventional ELMs. In this paper, a fast training algorithm (FTA-sELM) specially developed for sparse ELM is proposed, which improves training speed, achieves better generalization performance and further promotes the application of sparse ELM in large data problem. The proposed algorithm breaks the large quadratic programming (QP) problem of sparse ELM into a series of two-dimensional sub-QP problems, specifically. In every iteration, Newton’s method is employed to solve the optimal solution for each sub-QP problem. Moreover, a new clipping scheme for Lagrange multipliers is presented, which improves convergence performance.

Supported by a grant from China National Natural Science Foundation under Project of China (No. 61573335, U1811461, 91546122) and also a grant from China National Key Research and Development Program (No. 2017YFB1002104).

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Author information

Authors and Affiliations

  1. Department of management, China People’s Police University, Langfang, 065000, China

    Zhihong Miao

  2. Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology, CAS, Beijing, 100190, China

    Qing He

  3. University of Chinese Academy of Sciences, Beijing, 100049, China

    Qing He

Authors
  1. Zhihong Miao
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  2. Qing He
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Corresponding author

Correspondence to Zhihong Miao .

Editor information

Editors and Affiliations

  1. Institute of Information and Control, Hangzhou Dianzi University, Xiasha, Hangzhou, China

    Jiuwen Cao

  2. Department of Computer and Information Science, University of Macau, Taipa, Macao

    Chi Man Vong

  3. Nokia Bell Labs, Cybersecurity Research, Espoo, Finland

    Yoan Miche

  4. Department of Information and Logistics Technology, University of Houston, Houston, TX, USA

    Amaury Lendasse

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Miao, Z., He, Q. (2020). A Fast Algorithm for Sparse Extreme Learning Machine. In: Cao, J., Vong, C., Miche, Y., Lendasse, A. (eds) Proceedings of ELM 2018. ELM 2018. Proceedings in Adaptation, Learning and Optimization, vol 11. Springer, Cham. https://doi.org/10.1007/978-3-030-23307-5_7

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