Artificial Neural Networks and Machine Learning - ICANN 2011

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

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.

• biomedical image analysis
• kernel methods
• multimodal interfaces
• reinforcement learning
• self-organization
• algorithm analysis and problem complexity

• 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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