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Proceedings of ELM-2015 Volume 1

Theory, Algorithms and Applications (I)

  • Conference proceedings
  • © 2016

Overview

Editors:
  1. Jiuwen Cao

    1. Institute of Information and Contro, Hangzhou Dianzi University, Zhejiang, China

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  2. Kezhi Mao

    1. Nanyang Technological University, Singapore, Singapore

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  3. Jonathan Wu

    1. ECE, U of Windsor, WINDSOR, Canada

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  4. Amaury Lendasse

    1. Dept of Mechanical and Industrial Engg, University of Iowa, Iowa City, USA

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  • Focuses on the conference theme of Big Data Analysis, Machine Learning and Biological Learning
  • Results of the International Conference on Extreme Learning Machines (ELM-2015) held at Hangzhou, China, December 15-17, 2015
  • Presents Theory, Algorithms and Applications
  • Includes supplementary material: sn.pub/extras

Part of the book series: Proceedings in Adaptation, Learning and Optimization (PALO, volume 6)

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Table of contents (41 papers)

  1. Front Matter

    Pages i-ix
    Download chapter PDF

  2. Extreme Learning Machine for Multi-class Sentiment Classification of Tweets

    • Zhaoxia Wang, Yogesh Parth
    Pages 1-11

  3. Efficient Batch Parallel Online Sequential Extreme Learning Machine Algorithm Based on MapReduce

    • Shan Huang, Botao Wang, Yuemei Chen, Guoren Wang, Ge Yu
    Pages 13-25

  4. Fixed-Point Evaluation of Extreme Learning Machine for Classification

    • Yingnan Xu, Jingfei Jiang, Juping Jiang, Zhiqiang Liu, Jinwei Xu
    Pages 27-38

  5. Multi-layer Online Sequential Extreme Learning Machine for Image Classification

    • Bilal Mirza, Stanley Kok, Fei Dong
    Pages 39-49

  6. ELM Meets Urban Computing: Ensemble Urban Data for Smart City Application

    • Ningyu Zhang, Huajun Chen, Xi Chen, Jiaoyan Chen
    Pages 51-63

  7. Local and Global Unsupervised Kernel Extreme Learning Machine and Its Application in Nonlinear Process Fault Detection

    • Hanyuan Zhang, Xuemin Tian, Xiaohui Wang, Yuping Cao
    Pages 65-75

  8. Parallel Multi-graph Classification Using Extreme Learning Machine and MapReduce

    • Jun Pang, Yu Gu, Jia Xu, Xiaowang Kong, Ge Yu
    Pages 77-92

  9. Extreme Learning Machine for Large-Scale Graph Classification Based on MapReduce

    • Zhanghui Wang, Yuhai Zhao, Guoren Wang
    Pages 93-105

  10. The Distance-Based Representative Skyline Calculation Using Unsupervised Extreme Learning Machines

    • Mei Bai, Junchang Xin, Guoren Wang, Xite Wang
    Pages 107-119

  11. Multi-label Text Categorization Using \(L_{21}\)-norm Minimization Extreme Learning Machine

    • Mingchu Jiang, Na Li, Zhisong Pan
    Pages 121-133

  12. Cluster-Based Outlier Detection Using Unsupervised Extreme Learning Machines

    • Xite Wang, Derong Shen, Mei Bai, Tiezheng Nie, Yue Kou, Ge Yu
    Pages 135-146

  13. Segmentation of the Left Ventricle in Cardiac MRI Using an ELM Model

    • Yang Luo, Benqiang Yang, Lisheng Xu, Liling Hao, Jun Liu, Yang Yao et al.
    Pages 147-157

  14. Channel Estimation Based on Extreme Learning Machine for High Speed Environments

    • Fang Dong, Junbiao Liu, Liang He, Xiaohui Hu, Hong Liu
    Pages 159-167

  15. MIMO Modeling Based on Extreme Learning Machine

    • Junbiao Liu, Fang Dong, Jiuwen Cao, Xinyu Jin
    Pages 169-178

  16. Graph Classification Based on Sparse Graph Feature Selection and Extreme Learning Machine

    • Yajun Yu, Zhisong Pan, Guyu Hu
    Pages 179-191

  17. Time Series Prediction Based on Online Sequential Improved Error Minimized Extreme Learning Machine

    • Jiao Xue, Zeshen Liu, Yong Gong, Zhisong Pan
    Pages 193-209

  18. Adaptive Input Shaping for Flexible Systems Using an Extreme Learning Machine Algorithm Identification

    • Jun Hu, Zhongyi Chu
    Pages 211-225

  19. Kernel Based Semi-supervised Extreme Learning Machine and the Application in Traffic Congestion Evaluation

    • Qing Shen, Xiaojuan Ban, Chong Guo, Cong Wang
    Pages 227-236

  20. Improvement of ELM Algorithm for Multi-object Identification in Gesture Interaction

    • Liang Diao, Liguo Shuai, Huiling Chen, Weihang Zhu
    Pages 237-248
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Keywords

About this book

This book contains some selected papers from the International Conference on Extreme Learning Machine 2015, which was held in Hangzhou, China, December 15-17, 2015. This conference brought together researchers and engineers to share and exchange R&D experience on both theoretical studies and practical applications of the Extreme Learning Machine (ELM) technique and brain learning.

This book covers theories, algorithms ad applications of ELM. It gives readers a glance of the most recent advances of ELM. 

Editors and Affiliations

  • Institute of Information and Contro, Hangzhou Dianzi University, Zhejiang, China

    Jiuwen Cao

  • Nanyang Technological University, Singapore, Singapore

    Kezhi Mao

  • ECE, U of Windsor, WINDSOR, Canada

    Jonathan Wu

  • Dept of Mechanical and Industrial Engg, University of Iowa, Iowa City, USA

    Amaury Lendasse

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