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Artificial Neural Networks and Machine Learning - ICANN 2011

21st International Conference on Artificial Neural Networks, Espoo, Finland, June 14-17, 2011, Proceedings, Part I

  • Conference proceedings
  • © 2011

Overview

Editors:
  1. Timo Honkela

    1. Department of Information and Computer Science, Aalto University School of Science, Aalto, Finland

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  2. Włodzisław Duch

    1. School of Physics, Astronomy and Informatics, Department of Informatics, Nicolaus Copernicus University, Torun, Poland

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  3. Mark Girolami

    1. Department of Statistical Science, University College London, London, UK

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  4. Samuel Kaski

    1. Department of Information and Computer Science, Aalto University School of Science, Aalto, Finland

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 6791)

Part of the book sub series: Theoretical Computer Science and General Issues (LNTCS)

Included in the following conference series:

Conference proceedings info: ICANN 2011.

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Table of contents (47 papers)

  1. Front Matter

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  2. Transformation Equivariant Boltzmann Machines

    • Jyri J. Kivinen, Christopher K. I. Williams
    Pages 1-9

  3. Improved Learning of Gaussian-Bernoulli Restricted Boltzmann Machines

    • KyungHyun Cho, Alexander Ilin, Tapani Raiko
    Pages 10-17

  4. A Hierarchical Generative Model of Recurrent Object-Based Attention in the Visual Cortex

    • David P. Reichert, Peggy Series, Amos J. Storkey
    Pages 18-25

  5. ℓ1-Penalized Linear Mixed-Effects Models for BCI

    • Siamac Fazli, Márton Danóczy, Jürg Schelldorfer, Klaus-Robert Müller
    Pages 26-35

  6. Slow Feature Analysis - A Tool for Extraction of Discriminating Event-Related Potentials in Brain-Computer Interfaces

    • Sven Dähne, Johannes Höhne, Martijn Schreuder, Michael Tangermann
    Pages 36-43

  7. Transforming Auto-Encoders

    • Geoffrey E. Hinton, Alex Krizhevsky, Sida D. Wang
    Pages 44-51

  8. Stacked Convolutional Auto-Encoders for Hierarchical Feature Extraction

    • Jonathan Masci, Ueli Meier, Dan Cireşan, Jürgen Schmidhuber
    Pages 52-59

  9. Error-Backpropagation in Networks of Fractionally Predictive Spiking Neurons

    • Sander M. Bohte
    Pages 60-68

  10. ESN Intrinsic Plasticity versus Reservoir Stability

    • Petia Koprinkova-Hristova, Guenther Palm
    Pages 69-76

  11. Adaptive Routing Strategies for Large Scale Spiking Neural Network Hardware Implementations

    • Snaider Carrillo, Jim Harkin, Liam McDaid, Sandeep Pande, Seamus Cawley, Fearghal Morgan
    Pages 77-84

  12. Self-Organizing Map for the Multi-Goal Path Planning with Polygonal Goals

    • Jan Faigl, Libor Přeučil
    Pages 85-92

  13. Unlearning in the BCM Learning Rule for Plastic Self-organization in a Multi-modal Architecture

    • Mathieu Lefort, Yann Boniface, Bernard Girau
    Pages 93-100

  14. Neuronal Projections Can Be Sharpened by a Biologically Plausible Learning Mechanism

    • Matthew Cook, Florian Jug, Christoph Krautz
    Pages 101-108

  15. Explicit Class Structure by Weighted Cooperative Learning

    • Ryotaro Kamimura
    Pages 109-116

  16. Unsupervized Data-Driven Partitioning of Multiclass Problems

    • Hernán C. Ahumada, Guillermo L. Grinblat, Pablo M. Granitto
    Pages 117-125

  17. Bounds for Approximate Solutions of Fredholm Integral Equations Using Kernel Networks

    • Giorgio Gnecco, Věra Kůrková, Marcello Sanguineti
    Pages 126-133

  18. An Improved Training Algorithm for the Linear Ranking Support Vector Machine

    • Antti Airola, Tapio Pahikkala, Tapio Salakoski
    Pages 134-141

  19. Extending Tree Kernels with Topological Information

    • Fabio Aiolli, Giovanni Da San Martino, Alessandro Sperduti
    Pages 142-149

  20. Accelerating Kernel Neural Gas

    • Frank-Michael Schleif, Andrej Gisbrecht, Barbara Hammer
    Pages 150-158
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Other volumes

  1. Artificial Neural Networks and Machine Learning – ICANN 2011

  2. Artificial Neural Networks and Machine Learning – ICANN 2011

Keywords

About this book

This two volume set LNCS 6791 and LNCS 6792 constitutes the refereed proceedings of the 21th International Conference on Artificial Neural Networks, ICANN 2011, held in Espoo, Finland, in June 2011.
The 106 revised full or poster papers presented were carefully reviewed and selected from numerous submissions. ICANN 2011 had two basic tracks: brain-inspired computing and machine learning research, with strong cross-disciplinary interactions and applications.

Editors and Affiliations

  • Department of Information and Computer Science, Aalto University School of Science, Aalto, Finland

    Timo Honkela, Samuel Kaski

  • School of Physics, Astronomy and Informatics, Department of Informatics, Nicolaus Copernicus University, Torun, Poland

    Włodzisław Duch

  • Department of Statistical Science, University College London, London, UK

    Mark Girolami

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