Artificial Neural Networks and Machine Learning -- ICANN 2012

1. Front Matter

   PDF

2. Multilayer Perceptrons and Kernel Networks (A6)

   1. Complex-Valued Multilayer Perceptron Search Utilizing Eigen Vector Descent and Reducibility Mapping

      • Shinya Suzumura, Ryohei Nakano

      Pages 1-8

   2. Theoretical Analysis of Function of Derivative Term in On-Line Gradient Descent Learning

      • Kazuyuki Hara, Kentaro Katahira, Kazuo Okanoya, Masato Okada

      Pages 9-16

   3. Some Comparisons of Networks with Radial and Kernel Units

      • Věra Kůrková

      Pages 17-24

   4. Multilayer Perceptron for Label Ranking

      • Geraldina Ribeiro, Wouter Duivesteijn, Carlos Soares, Arno Knobbe

      Pages 25-32

   5. Electricity Load Forecasting: A Weekday-Based Approach

      • Irena Koprinska, Mashud Rana, Vassilios G. Agelidis

      Pages 33-41

3. Training and Learning (C4)

   1. Adaptive Exploration Using Stochastic Neurons

      • Michel Tokic, Günther Palm

      Pages 42-49

   2. Comparison of Long-Term Adaptivity for Neural Networks

      • Frank-Florian Steege, Horst-Michael Groß

      Pages 50-57

   3. Simplifying ConvNets for Fast Learning

      • Franck Mamalet, Christophe Garcia

      Pages 58-65

   4. A Modified Artificial Fish Swarm Algorithm for the Optimization of Extreme Learning Machines

      • João Fausto Lorenzato de Oliveira, Teresa B. Ludermir

      Pages 66-73

   5. Retracted: Robust Training of Feedforward Neural Networks Using Combined Online/Batch Quasi-Newton Techniques

      • Hiroshi Ninomiya

      Pages 74-83

   6. Estimating a Causal Order among Groups of Variables in Linear Models

      • Doris Entner, Patrik O. Hoyer

      Pages 84-91

   7. Training Restricted Boltzmann Machines with Multi-tempering: Harnessing Parallelization

      • Philemon Brakel, Sander Dieleman, Benjamin Schrauwen

      Pages 92-99

   8. A Computational Geometry Approach for Pareto-Optimal Selection of Neural Networks

      • Luiz C. B. Torres, Cristiano L. Castro, Antônio P. Braga

      Pages 100-107

   9. Learning Parameters of Linear Models in Compressed Parameter Space

      • Yohannes Kassahun, Hendrik Wöhrle, Alexander Fabisch, Marc Tabie

      Pages 108-115

   10. Control of a Free-Falling Cat by Policy-Based Reinforcement Learning

       • Daichi Nakano, Shin-ichi Maeda, Shin Ishii

       Pages 116-123

   11. Gated Boltzmann Machine in Texture Modeling

       • Tele Hao, Tapani Raiko, Alexander Ilin, Juha Karhunen

       Pages 124-131

   12. Neural PCA and Maximum Likelihood Hebbian Learning on the GPU

       • Pavel Krömer, Emilio Corchado, Václav Snášel, Jan Platoš, Laura García-Hernández

       Pages 132-139

4. Inference and Recognition (C5)

   1. Construction of Emerging Markets Exchange Traded Funds Using Multiobjective Particle Swarm Optimisation

      • Marta Díez-Fernández, Sergio Alvarez Teleña, Denise Gorse

      Pages 140-147

   2. The Influence of Supervised Clustering for RBFNN Centers Definition: A Comparative Study

      • André R. Gonçalves, Rosana Veroneze, Salomão Madeiro, Carlos R. B. Azevedo, Fernando J. Von Zuben

      Pages 148-155

The two-volume set LNCS 7552 + 7553 constitutes the proceedings of the 22nd International Conference on Artificial Neural Networks, ICANN 2012, held in Lausanne, Switzerland, in September 2012. The 162 papers included in the proceedings were carefully reviewed and selected from 247 submissions. They are organized in topical sections named: theoretical neural computation; information and optimization; from neurons to neuromorphism; spiking dynamics; from single neurons to networks; complex firing patterns; movement and motion; from sensation to perception; object and face recognition; reinforcement learning; bayesian and echo state networks; recurrent neural networks and reservoir computing; coding architectures; interacting with the brain; swarm intelligence and decision-making; mulitlayer perceptrons and kernel networks; training and learning; inference and recognition; support vector machines; self-organizing maps and clustering; clustering, mining and exploratory analysis; bioinformatics; and time weries and forecasting.

• brain-computer interface
• combinatorial optimization
• evolutionary algorithm
• particle swarm
• self-organizing maps
• algorithm analysis and problem complexity

• Neuro Heuristic Research Group, University of Lausanne, Lausanne, Switzerland

  Alessandro E. P. Villa

• Department of Informatics, Nicolaus Copernicus University, Toruń, Poland

  Włodzisław Duch

• Center for Complex Systems Studies, Kalamazoo College, Kalamazoo, USA

  Péter Érdi

• Dipartimento di Informatica e Scienze dell’Informazione, Università di Genova, Genoa, Italy

  Francesco Masulli

• Institut für Neuroinformatik, Universität Ulm, Ulm, Germany

  Günther Palm

Policies and ethics