Extreme Learning Machines 2013: Algorithms and Applications

  • Fuchen Sun
  • Kar-Ann Toh
  • Manuel Grana Romay
  • Kezhi Mao

Part of the Adaptation, Learning, and Optimization book series (ALO, volume 16)

Table of contents

  1. Front Matter
    Pages i-vi
  2. David Becerra-Alonso, Mariano Carbonero-Ruz, Alfonso Carlos Martínez-Estudillo, Francisco José Marténez-Estudillo
    Pages 1-12
  3. Zhiyong Zeng, YunLiang Jiang, Yong Liu, Weicong Liu
    Pages 13-23
  4. Wentao Zhu, Jun Miao, Laiyun Qing
    Pages 25-34
  5. Chengzhang Zhu, Jianping Yin, Qian Li
    Pages 67-79
  6. Inchio Lou, Zhengchao Xie, Wai Kin Ung, Kai Meng Mok
    Pages 95-111
  7. Baiyou Qiao, Yang Chen, Hong Wang, Donghai Chen, Yanning Hua, Han Dong et al.
    Pages 113-134
  8. Iñigo Barandiaran, Odei Maiz, Ion Marqués, Jurgui Ugarte, Manuel Graña
    Pages 135-143
  9. Ying Liu, Tengqi Ye, Guoqi Liu, Cathal Gurrin, Bin Zhang
    Pages 145-165
  10. J. David Nuñez-Gonzalez, Manuel Graña
    Pages 179-187
  11. Yansha Guo, Yiqiang Chen, Junfa Liu
    Pages 189-207
  12. Charu Agarwal, Anurag Mishra, Arpita Sharma, Girija Chetty
    Pages 209-225

About this book


In recent years, ELM has emerged as a revolutionary technique of computational intelligence, and has attracted considerable attentions. An extreme learning machine (ELM) is a single layer feed-forward neural network alike learning system, whose connections from the input layer to the hidden layer are randomly generated, while the connections from the hidden layer to the output layer are learned through linear learning methods. The outstanding merits of extreme learning machine (ELM) are its fast learning speed, trivial human intervene and high scalability.  

This book contains some selected papers from the International Conference on Extreme Learning Machine 2013, which was held in Beijing China, October 15-17, 2013. This conference aims to bring together the researchers and practitioners of extreme learning machine from a variety of fields including artificial intelligence, biomedical engineering and bioinformatics, system modelling and control, and signal and image processing, to promote research and discussions of “learning without iterative tuning".

This book covers algorithms and applications of ELM. It gives readers a glance of the newest developments of ELM.  


Computational Intelligence Extreme Learning Machines Kernel Based Algorithms Real-Time Learning/Reasoning Robustness and Stability Analysis Sequential and Incremental Learning Universal Approximation and Convergence

Editors and affiliations

  • Fuchen Sun
    • 1
  • Kar-Ann Toh
    • 2
  • Manuel Grana Romay
    • 3
  • Kezhi Mao
    • 4
  1. 1.Department of Computer Science and TechnologyTsinghua UniversityBeijingChina
  2. 2.School of Electrical and Electronic EngineeringYonsei UniversitySeoulKorea, Republic of (South Korea)
  3. 3.Department of Computer Science and Artificial IntelligenceUniversidad Del Pais VascoSan SebastianSpain
  4. 4.School of Electrical and Electronic EngineeringNanyang Technological UniversitySingaporeSingapore

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-04741-6
  • Copyright Information Springer International Publishing Switzerland 2014
  • Publisher Name Springer, Cham
  • eBook Packages Engineering
  • Print ISBN 978-3-319-04740-9
  • Online ISBN 978-3-319-04741-6
  • Series Print ISSN 1867-4534
  • Series Online ISSN 1867-4542
  • About this book