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© 2019

Artificial Neural Networks and Machine Learning – ICANN 2019: Workshop and Special Sessions

28th International Conference on Artificial Neural Networks, Munich, Germany, September 17–19, 2019, Proceedings

  • Igor V. Tetko
  • Věra Kůrková
  • Pavel Karpov
  • Fabian Theis
Conference proceedings ICANN 2019

Part of the Lecture Notes in Computer Science book series (LNCS, volume 11731)

Also part of the Theoretical Computer Science and General Issues book sub series (LNTCS, volume 11731)

Table of contents

  1. Front Matter
    Pages i-xxxii
  2. Workshop: Reservoir Computing - Methodology

    1. Front Matter
      Pages 1-6
    2. Stephan Tietz, Doreen Jirak, Stefan Wermter
      Pages 7-18
    3. Anthony Strock, Nicolas Rougier, Xavier Hinaut
      Pages 19-23
    4. Felix Meyer zu Driehausen, Rüdiger Busche, Johannes Leugering, Gordon Pipa
      Pages 24-34
    5. Taisuke Kobayashi, Toshiki Sugino
      Pages 35-47
    6. Giuseppe Franco, Luca Cerina, Claudio Gallicchio, Alessio Micheli, Marco Domenico Santambrogio
      Pages 48-61
    7. Claudio Gallicchio, Alessio Micheli
      Pages 62-75
    8. Takanori Akiyama, Gouhei Tanaka
      Pages 82-88
    9. Pietro Verzelli, Cesare Alippi, Lorenzo Livi
      Pages 89-93
    10. Alexander Popov, Petia Koprinkova-Hristova, Kiril Simov, Petya Osenova
      Pages 94-109
    11. Rajkumar Ramamurthy, Robin Stenzel, Rafet Sifa, Anna Ladi, Christian Bauckhage
      Pages 110-120
    12. Mantas Lukoševičius, Arnas Uselis
      Pages 121-133
  3. Workshop: Reservoir Computing - Physical Implementations

    1. Front Matter
      Pages 135-135
    2. Tomoyuki Kubota, Kohei Nakajima, Hirokazu Takahashi
      Pages 137-148
    3. Jean-Pierre Locquet, PHRESCO Partners
      Pages 149-155
    4. Piotr Antonik, Nicolas Marsal, Daniel Brunner, Damien Rontani
      Pages 156-160
    5. Stijn Sackesyn, Chonghuai Ma, Andrew Katumba, Joni Dambre, Peter Bienstman
      Pages 161-164
    6. Jean Benoit Héroux, Naoki Kanazawa, Piotr Antonik
      Pages 165-169

Other volumes

  1. 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17–19, 2019, Proceedings, Part I
  2. 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17–19, 2019, Proceedings, Part II
  3. 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17–19, 2019, Proceedings, Part III
  4. 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17–19, 2019, Proceedings, Part IV
  5. Artificial Neural Networks and Machine Learning – ICANN 2019: Workshop and Special Sessions
    28th International Conference on Artificial Neural Networks, Munich, Germany, September 17–19, 2019, Proceedings

About these proceedings

Introduction

The proceedings set LNCS 11727, 11728, 11729, 11730, and 11731 constitute the proceedings of the 28th International Conference on Artificial Neural Networks, ICANN 2019, held in Munich, Germany, in September 2019. 
The total of 277 full papers and 43 short papers presented in these proceedings was carefully reviewed and selected from 494 submissions. They were organized in 5 volumes focusing on theoretical neural computation; deep learning; image processing; text and time series; and workshop and special sessions. 

Keywords

artificial intelligence classification clustering computer networks echo state networks image processing image reconstruction image segmentation learning algorithms machine learning neural networks optical communication photonics recurrent neural networks Reservoir Computing semantics signal processing Support Vector Machines (SVM) telecommunication networks telecommunication traffic

Editors and affiliations

  1. 1.Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH)NeuherbergGermany
  2. 2.Institute of Computer ScienceCzech Academy of SciencesPrague 8Czech Republic
  3. 3.Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH)NeuherbergGermany
  4. 4.Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH)NeuherbergGermany

Bibliographic information