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Fix-Budget and Recurrent Data Mining for Online Haptic Perception

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Neural Information Processing (ICONIP 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10638))

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Abstract

Haptic perception is to identify different targets from haptic input. Haptic data have two prominent features: sequentially real-time and temporally correlated, which calls for a fixed-budget and recurrent perception procedure. Based on an efficient-robust spatio-temporal feature representation, we handle the problem with a bounded online-sequential learning framework (MBS-ESN), and incorporates the strength of batch-regularization bootstrapping, bounded recursive reservoir, and momentum-based estimation. Experimental evaluations show that it outperforms the state-of-the-art methods by a large margin on test accuracy; and its training performance is superior to most compared models from aspects of computational complexity and storage efficiency.

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Acknowledgments

This work is supported by National Natural Science Foundation of China with grant number 041320190.

Author information

Authors and Affiliations

  1. Department of Computer Science and Technology, Tsinghua University, Beijing, 100084, China

    Lele Cao, Fuchun Sun, Xiaolong Liu & Wenbing Huang

  2. Department of Computing and Information Systems, The University of Melbourne, Melbourne, VIC, 3010, Australia

    Lele Cao, Weihao Cheng & Ramamohanarao Kotagiri

Authors
  1. Lele Cao
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  2. Fuchun Sun
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  3. Xiaolong Liu
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  4. Wenbing Huang
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  5. Weihao Cheng
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  6. Ramamohanarao Kotagiri
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Corresponding author

Correspondence to Lele Cao .

Editor information

Editors and Affiliations

  1. Guangdong University of Technology, Guangzhou, China

    Derong Liu

  2. Guangdong University of Technology, Guangzhou, China

    Shengli Xie

  3. South China University of Technology, Guangzhou, China

    Yuanqing Li

  4. Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Dongbin Zhao

  5. King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia

    El-Sayed M. El-Alfy

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Cao, L., Sun, F., Liu, X., Huang, W., Cheng, W., Kotagiri, R. (2017). Fix-Budget and Recurrent Data Mining for Online Haptic Perception. In: Liu, D., Xie, S., Li, Y., Zhao, D., El-Alfy, ES. (eds) Neural Information Processing. ICONIP 2017. Lecture Notes in Computer Science(), vol 10638. Springer, Cham. https://doi.org/10.1007/978-3-319-70139-4_59

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  • DOI: https://doi.org/10.1007/978-3-319-70139-4_59

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-70138-7

  • Online ISBN: 978-3-319-70139-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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