Neural Information Processing

23rd International Conference, ICONIP 2016, Kyoto, Japan, October 16–21, 2016, Proceedings, Part II

  • Akira Hirose
  • Seiichi Ozawa
  • Kenji Doya
  • Kazushi Ikeda
  • Minho Lee
  • Derong Liu

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9948)

Also part of the Theoretical Computer Science and General Issues book sub series (LNTCS, volume 9948)

Table of contents

  1. Front Matter
    Pages I-XIX
  2. Machine Learning

    1. Front Matter
      Pages 1-1
    2. Hideitsu Hino, Ken Takano, Shotaro Akaho, Noboru Murata
      Pages 3-10
    3. Hideitsu Hino, Shotaro Akaho, Noboru Murata
      Pages 11-19
    4. Takashi Fujii, Hidetaka Ito, Seiji Miyoshi
      Pages 28-36
    5. Rohitash Chandra, Abhishek Gupta, Yew-Soon Ong, Chi-Keong Goh
      Pages 37-46
    6. Kazuyuki Hara, Daisuke Saitoh, Takumi Kondou, Satoshi Suzuki, Hayaru Shouno
      Pages 66-73
    7. Gwenaelle Cunha Sergio, Minho Lee
      Pages 74-81
    8. Anupriya Gogna, Angshul Majumdar
      Pages 82-89
    9. Javaria Ikram, Yao Lu, Jianwu Li, Nie Hui
      Pages 98-107
    10. Hiroaki Sasaki, Yurina Ono, Masashi Sugiyama
      Pages 108-116
    11. Duy-Khuong Nguyen, Quoc Tran-Dinh, Tu-Bao Ho
      Pages 117-125
    12. Vinícius R. Máximo, Mariá C. V. Nascimento, Fabricio A. Breve, Marcos G. Quiles
      Pages 126-135
    13. Anupriya Gogna, Angshul Majumdar
      Pages 144-151

Other volumes

  1. 23rd International Conference, ICONIP 2016, Kyoto, Japan, October 16–21, 2016, Proceedings, Part I
  2. Neural Information Processing
    23rd International Conference, ICONIP 2016, Kyoto, Japan, October 16–21, 2016, Proceedings, Part II
  3. 23rd International Conference, ICONIP 2016, Kyoto, Japan, October 16–21, 2016, Proceedings, Part III
  4. 23rd International Conference, ICONIP 2016, Kyoto, Japan, October 16–21, 2016, Proceedings, Part IV

About these proceedings

Introduction

The four volume set LNCS 9947, LNCS 9948, LNCS 9949, and LNCS 9950 constitues the proceedings of the 23rd International Conference on Neural Information Processing, ICONIP 2016, held in Kyoto, Japan, in October 2016. The 296 full papers presented were carefully reviewed and selected from 431 submissions. The 4 volumes are organized in topical sections on deep and reinforcement learning; big data analysis; neural data analysis; robotics and control; bio-inspired/energy efficient information processing; whole brain architecture; neurodynamics; bioinformatics; biomedical engineering; data mining and cybersecurity workshop; machine learning; neuromorphic hardware; sensory perception; pattern recognition; social networks; brain-machine interface; computer vision; time series analysis; data-driven approach for extracting latent features; topological and graph based clustering methods; computational intelligence; data mining; deep neural networks; computational and cognitive neurosciences; theory and algorithms.

 

Keywords

embedded systems genetic algorithms neural networks pattern recognition swarm intelligence big data biometric authentication brain-computer interface cellular neural network cloud computing computational intelligence data mining evolutionary algorithm image semantics natural language processing particle swarm optimization recommender system self-organizing maps

Editors and affiliations

  • Akira Hirose
    • 1
  • Seiichi Ozawa
    • 2
  • Kenji Doya
    • 3
  • Kazushi Ikeda
    • 4
  • Minho Lee
    • 5
  • Derong Liu
    • 6
  1. 1.The University of TokyoTokyoJapan
  2. 2.Kobe UniversityKobeJapan
  3. 3.Okinawa Institute of Science and Technology Graduate UniversityOnnaJapan
  4. 4.Nara Institute of Science and TechnologyIkomaJapan
  5. 5.Kyungpook National UniversityDaeguKorea (Republic of)
  6. 6.Chinese Academy of SciencesBeijingChina

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-46672-9
  • Copyright Information Springer International Publishing AG 2016
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-46671-2
  • Online ISBN 978-3-319-46672-9
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • About this book