17. ICANN 2007:
Porto,
Portugal
Joaquim Marques de Sá, Luís A. Alexandre, Wlodzislaw Duch, Danilo P. Mandic (Eds.):
Artificial Neural Networks - ICANN 2007, 17th International Conference, Porto, Portugal, September 9-13, 2007, Proceedings, Part I.
Lecture Notes in Computer Science 4668 Springer 2007, ISBN 978-3-540-74689-8 
Learning Theory
- Shinichi Nakajima, Sumio Watanabe:
Generalization Error of Automatic Relevance Determination.
1-10
- Takeshi Matsuda, Sumio Watanabe:
On a Singular Point to Contribute to a Learning Coefficient and Weighted Resolution of Singularities.
11-18
- Stefan Babinec, Jiri Pospichal:
Improving the Prediction Accuracy of Echo State Neural Networks by Anti-Oja's Learning.
19-28
- Yu Nishiyama, Sumio Watanabe:
Theoretical Analysis of Accuracy of Gaussian Belief Propagation.
29-38
- Héctor F. Satizábal, Andrés Pérez-Uribe:
Relevance Metrics to Reduce Input Dimensions in Artificial Neural Networks.
39-48
- Feng Liu, Fengzhan Tian, QiLiang Zhu:
An Improved Greedy Bayesian Network Learning Algorithm on Limited Data.
49-57
- Rowland R. Sillito, Robert B. Fisher:
Incremental One-Class Learning with Bounded Computational Complexity.
58-67
- Georgios Lappas:
Estimating the Size of Neural Networks from the Number of Available Training Data.
68-77
- Yiu-ming Cheung, Hong Zeng:
A Maximum Weighted Likelihood Approach to Simultaneous Model Selection and Feature Weighting in Gaussian Mixture.
78-87
- Ryosuke Iriguchi, Sumio Watanabe:
Estimation of Poles of Zeta Function in Learning Theory Using Padé Approximation.
88-97
- M. A. H. Akhand, Kazuyuki Murase:
Neural Network Ensemble Training by Sequential Interaction.
98-108
- Daniel Schneegaß, Steffen Udluft, Thomas Martinetz:
Improving Optimality of Neural Rewards Regression for Data-Efficient Batch Near-Optimal Policy Identification.
109-118
Advances in Neural Network Learning Methods
- Anton Schwaighofer, Mathäus Dejori, Volker Tresp, Martin Stetter:
Structure Learning with Nonparametric Decomposable Models.
119-128
- Jiri Grim, Jan Hora:
Recurrent Bayesian Reasoning in Probabilistic Neural Networks.
129-138
- Thorsten Suttorp, Christian Igel:
Resilient Approximation of Kernel Classifiers.
139-148
- Koichiro Yamauchi, Masayoshi Sato:
Incremental Learning of Spatio-temporal Patterns with Model Selection.
149-158
- Daniel García, Ana M. González, José R. Dorronsoro:
Accelerating Kernel Perceptron Learning.
159-168
- Akihide Horita, Kenji Nakayama, Akihiro Hirano:
Analysis and Comparative Study of Source Separation Performances in Feed-Forward and Feed-Back BSSs Based on Propagation Delays in Convolutive Mixture.
169-179
- Marek Grochowski, Wlodzislaw Duch:
Learning Highly Non-separable Boolean Functions Using Constructive Feedforward Neural Network.
180-189
- Bertha Guijarro-Berdiñas, Oscar Fontenla-Romero, Beatriz Pérez-Sánchez, Paula Fraguela:
A Fast Semi-linear Backpropagation Learning Algorithm.
190-198
- Abderrahmane Boubezoul, Sébastien Paris, Mustapha Ouladsine:
Improving the GRLVQ Algorithm by the Cross Entropy Method.
199-208
- Enrique Romero, Ignacio Barrio, Lluís Belanche:
Incremental and Decremental Learning for Linear Support Vector Machines.
209-218
- Cláudio M. S. Medeiros, Guilherme De A. Barreto:
An Efficient Method for Pruning the Multilayer Perceptron Based on the Correlation of Errors.
219-228
- Yuki Taniguchi, Takeshi Mori, Shin Ishii:
Reinforcement Learning for Cooperative Actions in a Partially Observable Multi-agent System.
229-238
- Jarkko Tikka:
Input Selection for Radial Basis Function Networks by Constrained Optimization.
239-248
- Stefan Duffner, Christophe Garcia:
An Online Backpropagation Algorithm with Validation Error-Based Adaptive Learning Rate.
249-258
- Chun-Cheng Peng, George D. Magoulas:
Adaptive Self-scaling Non-monotone BFGS Training Algorithm for Recurrent Neural Networks.
259-268
- Paul F. Evangelista, Mark J. Embrechts, Boleslaw K. Szymanski:
Some Properties of the Gaussian Kernel for One Class Learning.
269-278
- Antonino Fiannaca, Giuseppe Di Fatta, Salvatore Gaglio, Riccardo Rizzo, Alfonso Urso:
Improved SOM Learning Using Simulated Annealing.
279-288
- Roselito de Albuquerque Teixeira, Antônio de Pádua Braga, Rodney R. Saldanha, Ricardo H. C. Takahashi, Talles Henrique de Medeiros:
The Usage of Golden Section in Calculating the Efficient Solution in Artificial Neural Networks Training by Multi-objective Optimization.
289-298
Ensemble Learning
Spiking Neural Networks
Advances in Neural Network Architectures
- Wolfgang Hübner, Hanspeter A. Mallot:
Deformable Radial Basis Functions.
411-420
- Ignacio Barrio, Enrique Romero, Lluís Belanche:
Selection of Basis Functions Guided by the L2 Soft Margin.
421-430
- Ignacio Barrio, Enrique Romero, Lluís Belanche:
Extended Linear Models with Gaussian Prior on the Parameters and Adaptive Expansion Vectors.
431-440
- Qinggang Meng, Baihua Li, Nicholas Costen, Horst Holstein:
Functional Modelling of Large Scattered Data Sets Using Neural Networks.
441-449
- Joaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo:
Stacking MF Networks to Combine the Outputs Provided by RBF Networks.
450-459
- Simon McGregor:
Neural Network Processing for Multiset Data.
460-470
- Benjamin Schrauwen, Jeroen Defour, David Verstraeten, Jan M. Van Campenhout:
The Introduction of Time-Scales in Reservoir Computing, Applied to Isolated Digits Recognition.
471-479
- Ryotaro Kamimura:
Partially Activated Neural Networks by Controlling Information.
480-489
- K. Murugesan, P. Elango:
CNN Based Hole Filler Template Design Using Numerical Integration Techniques.
490-500
- Ralf Eickhoff, Tim Kaulmann, Ulrich Rückert:
Impact of Shrinking Technologies on the Activation Function of Neurons.
501-510
- Vicenç Soler, Marta Prim:
Rectangular Basis Functions Applied to Imbalanced Datasets.
511-519
- Xavier Parra, Andreu Català:
Qualitative Radial Basis Function Networks Based on Distance Discretization for Classification Problems.
520-528
- Tim Kaulmann, Axel Löffler, Ulrich Rückert:
A Control Approach to a Biophysical Neuron Model.
529-538
- Héctor Mesa, Francisco J. Veredas:
Integrate-and-Fire Neural Networks with Monosynaptic-Like Correlated Activity.
539-548
- Alex Graves, Santiago Fernández, Jürgen Schmidhuber:
Multi-dimensional Recurrent Neural Networks.
549-558
- Giuliano Grossi, Federico Pedersini:
FPGA Implementation of an Adaptive Stochastic Neural Model.
559-568
Neural Dynamics and Complex Systems
- Yonggui Kao, Qinghe Ming:
Global Robust Stability of Competitive Neural Networks with Continuously Distributed Delays and Different Time Scales.
569-578
- Javier Iglesias, Olga K. Chibirova, Alessandro E. P. Villa:
Nonlinear Dynamics Emerging in Large Scale Neural Networks with Ontogenetic and Epigenetic Processes.
579-588
- Juan J. Fuertes-Martínez, Miguel A. Prada, Manuel Domínguez-González, Perfecto Reguera-Acevedo, Ignacio Díaz Blanco, Abel A. Cuadrado Vega:
Modeling of Dynamics Using Process State Projection on the Self Organizing Map.
589-598
- Marie Kratz, Miguel A. Atencia Ruiz, Gonzalo Joya Caparrós:
Fixed Points of the Abe Formulation of Stochastic Hopfield Networks.
599-608
- Ignacio Díaz Blanco, Abel A. Cuadrado Vega, Alberto B. Diez González, Juan J. Fuertes-Martínez, Manuel Domínguez-González, Perfecto Reguera-Acevedo:
Visualization of Dynamics Using Local Dynamic Modelling with Self Organizing Maps.
609-617
- Michal Cernanský, Peter Tino:
Comparison of Echo State Networks with Simple Recurrent Networks and Variable-Length Markov Models on Symbolic Sequences.
618-627
Data Analysis
- Changjian Huang, Mark J. Embrechts, Nagamani Sukumar, Curt M. Breneman:
Data Fusion and Auto-fusion for Quantitative Structure-Activity Relationship (QSAR).
628-637
- Leonid B. Litinskii:
Cluster Domains in Binary Minimization Problems.
638-647
- Leonardo Franco, José Luis Subirats, José M. Jerez:
MaxSet: An Algorithm for Finding a Good Approximation for the Largest Linearly Separable Set.
648-656
- Jörg Lücke, Maneesh Sahani:
Generalized Softmax Networks for Non-linear Component Extraction.
657-667
- Ying Wu, Colin Fyfe, Pei Ling Lai:
Stochastic Weights Reinforcement Learning for Exploratory Data Analysis.
668-676
- Zoltán Szabó, Barnabás Póczos, Gábor Szirtes, András Lörincz:
Post Nonlinear Independent Subspace Analysis.
677-686
Estimation
- Kenji Nagata, Sumio Watanabe:
Algebraic Geometric Study of Exchange Monte Carlo Method.
687-696
- Daan Wierstra, Alexander Förster, Jan Peters, Jürgen Schmidhuber:
Solving Deep Memory POMDPs with Recurrent Policy Gradients.
697-706
- Ezequiel López-Rubio, Juan Miguel Ortiz-de-Lazcano-Lobato, Domingo López-Rodríguez, María del Carmen Vargas-González:
Soft Clustering for Nonparametric Probability Density Function Estimation.
707-716
- Yasuaki Kuroe, Hajimu Kawakami:
Vector Field Approximation by Model Inclusive Learning of Neural Networks.
717-726
- Javier González, Alberto Muñoz:
Spectral Measures for Kernel Matrices Comparison.
727-736
- David A. Elizondo, Juan Miguel Ortiz-de-Lazcano-Lobato, Ralph Birkenhead:
A Novel and Efficient Method for Testing Non Linear Separability.
737-746
- Nikolay Y. Nikolaev, Evgueni N. Smirnov:
A One-Step Unscented Particle Filter for Nonlinear Dynamical Systems.
747-756
Spatial and Spatio-Temporal Learning
Evolutionary Computing
Meta Learning, Agents Learning
Complex-Valued Neural Networks (Special Session)
Temporal Synchronization and Nonlinear Dynamics in Neural Networks (Special Session)
- Sven Rebhan, Julian Eggert, Horst-Michael Groß, Edgar Körner:
Sparse and Transformation-Invariant Hierarchical NMF.
894-903
- Raul Vicente, Gordon Pipa, Ingo Fischer, Claudio R. Mirasso:
Zero-Lag Long Range Synchronization of Neurons Is Enhanced by Dynamical Relaying.
904-913
- Giovanni Egidio Pazienza, Eduardo Gómez-Ramírez, Xavier Vilasís-Cardona:
Polynomial Cellular Neural Networks for Implementing the Game of Life.
914-923
- Yoshiyuki Asai, Takashi Yokoi, Alessandro E. P. Villa:
Deterministic Nonlinear Spike Train Filtered by Spiking Neuron Model.
924-933
- Matthieu Lagarde, Pierre Andry, Philippe Gaussier:
The Role of Internal Oscillators for the One-Shot Learning of Complex Temporal Sequences.
934-943
- Jan-Hendrik Schleimer, Ricardo Vigário:
Clustering Limit Cycle Oscillators by Spectral Analysis of the Synchronisation Matrix with an Additional Phase Sensitive Rotation.
944-953
- Manish Dev Shrimali, Guoguang He, Sudeshna Sinha, Kazuyuki Aihara:
Control and Synchronization of Chaotic Neurons Under Threshold Activated Coupling.
954-962
- Cristina Masoller, M. C. Torrent, Jordi García-Ojalvo:
Neuronal Multistability Induced by Delay.
963-972
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