ESANN 2007:
Bruges,
Belgium
ESANN 2007, 15th European Symposium on Artificial Neural Networks, Bruges, Belgium, April 25-27, 2007, Proceedings.
2007 BibTeX
Dynamic and complex systems
Prototype-based learning
Model selection and regularization
Fuzzy and Probalistic Methods in Neural Networks and Machine Learning
Learning I
- Maite García-Sebastián, Manuel Graña:
SOM for intensity inhomogeneity correction in MRI.
109-114
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- Antti Sorjamaa, Paul Merlin, Bertrand Maillet, Amaury Lendasse:
SOM+EOF for finding missing values.
115-120
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- Hassan Ghaziri:
Self-organized chains for clustering.
121-126
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- Aree Witoelar, Michael Biehl, Anarta Ghosh, Barbara Hammer:
On the dynamics of Vector Quantization and Neural Gas.
127-132
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- Alexander Yudashkin:
Three-dimensional self-organizing dynamical systems for discrete structures memorizing and retrieval.
133-138
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- Murilo Coelho Naldi, André Carlos Ponce Leon Ferreira de Carvalho:
Clustering using genetic algorithm combining validation criteria.
139-144
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- Thomas Girod, Laurent Bougrain, Frédéric Alexandre:
Toward a robust 2D spatio-temporal self-organization.
145-150
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- Tomasz Talaska, Rafal Dlugosz, Witold Pedrycz:
Adaptive Weight Change Mechanism for Kohonens's Neural Network Implemented in CMOS 0.18 um Technology.
151-156
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- Catherine Krier, Damien François, Fabrice Rossi, Michel Verleysen:
Feature clustering and mutual information for the selection of variables in spectral data.
157-162
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- Bernardo Penna Resende de Carvalho, Ricardo de Souza Ribeiro, Talles Henrique de Medeiros:
Prediction of post-synaptic activity in proteins using recursive feature elimination.
163-168
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- Piyang Wang, Tommy W. S. Chow:
A new feature selection scheme using data distribution factor for transactional data.
169-174
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- Gaetano Liborio Aiello, Carlo Casarino:
Informational cost in correlation-based neuronal networks.
175-179
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- Ulrich Rückert, Ralf Eickhoff:
Controlling complexity of RBF networks by similarity.
181-186
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- Dirk Gorissen, Wouter Hendrickx, Tom Dhaene:
Adaptive Global Metamodeling with Neural Networks.
187-192
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Convex Optimization for the Design of Learning Machines
Generative models and maximum likelihood approaches
Kernel methods and Support Vector Machines
Reinforcement Learning
- Verena Heidrich-Meisner, Martin Lauer, Christian Igel, Martin A. Riedmiller:
Reinforcement learning in a nutshell.
277-288
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- Manuel Loth, Philippe Preux, Manuel Davy:
A unified view of TD algorithms, introducing Full-gradient TD and Equi-gradient descent TD.
289-294
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- Jan Peters, Stefan Schaal:
Applying the Episodic Natural Actor-Critic Architecture to Motor Primitive Learning.
295-300
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- Daniel Schneegaß, Steffen Udluft, Thomas Martinetz:
Neural Rewards Regression for near-optimal policy identification in Markovian and partial observable environments.
301-306
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- Colin Fyfe, Pei Ling Lai:
Immediate Reward Reinforcement Learning for Projective Kernel Methods.
307-312
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- Kary Främling:
Replacing eligibility trace for action-value learning with function approximation.
313-318
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- Anton Maximilian Schäfer, Steffen Udluft, Hans-Georg Zimmermann:
The Recurrent Control Neural Network.
319-324
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Learning II
- Daniel Schneegaß, Anton Maximilian Schäfer, Thomas Martinetz:
The Intrinsic Recurrent Support Vector Machine.
325-330
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- Bernardo Penna Resende de Carvalho, Antônio de Pádua Braga:
A-LSSVM: an Adaline based iterative sparse LS-SVM classifier.
331-336
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- Daniel Schneegaß, Steffen Udluft, Thomas Martinetz:
Explicit Kernel Rewards Regression for data-efficient near-optimal policy identification.
337-342
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- Sumeet Agarwal, V. Vijaya Saradhi, Harish Karnick:
Kernel-based online machine learning and support vector reduction.
343-348
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- Zsolt Minier, Lehel Csató:
Kernel PCA based clustering for inducing features in text categorization.
349-354
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- Frederic Suard, Alain Rakotomamonjy, Abdelaziz Benrshrair:
Kernel on Bag of Paths For Measuring Similarity of Shapes.
355-360
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- Francesc Benimeli, Ken Sharman:
Electroencephalogram signal classification for brain computer interfaces using wavelets and support vector machines.
361-366
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- Bertrand Fontaine, Herbert Peremans, Benjamin Schrauwen:
Bat echolocation modelling using spike kernels with Support Vector Regression.
367-372
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- Terry Windeatt:
Ensemble neural classifier design for face recognition.
373-378
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- J. Salvador Sánchez, Ludmila I. Kuncheva:
Data reduction using classifier ensembles.
379-384
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- Patrick Kouontchou, Bertrand Maillet:
ICA-based High Frequency VaR for Risk Management.
385-390
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- Travis Wiens, Rich Burton, Greg Schoenau:
Algebraic inversion of an artificial neural network classifier.
391-396
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- Karina Zapien Arreola, Gilles Gasso, Stéphane Canu:
Estimation of tangent planes for neighborhood graph correction.
397-402
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- Madalina Olteanu, Joseph Rynkiewicz:
Estimating the Number of Components in a Mixture of Multilayer Perceptrons.
403-408
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Biologically motivated learning
Learning causality
Reservoir Computing
- Benjamin Schrauwen, David Verstraeten, Jan M. Van Campenhout:
An overview of reservoir computing: theory, applications and implementations.
471-482
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- Huaien Gao, Rudolf Sollacher, Hans-Peter Kriegel:
Spiral Recurrent Neural Network for Online Learning.
483-488
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- Jochen J. Steil:
Several ways to solve the MSO problem.
489-494
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- David Verstraeten, Benjamin Schrauwen, Dirk Stroobandt:
Adapting reservoir states to get Gaussian distributions.
495-500
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- Carlos Lourenço:
Structured reservoir computing with spatiotemporal chaotic attractors.
501-506
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- Xavier Dutoit, Hendrik Van Brussel, Marnix Nuttin:
A first attempt of reservoir pruning for classification problems.
507-512
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- Marion Wardermann, Jochen J. Steil:
Intrinsic plasticity for reservoir learning algorithms.
513-518
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Learning III
- Eva Kaslik, Stefan Balint:
Bifurcation analysis for a discrete-time Hopfield neural network of two neurons with two delays.
519-524
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- José Antonio Gómez-Ruiz, José Muñoz-Pérez, M. Angeles García-Bernal, Ezequiel López-Rubio:
Spicules-based competitive neural network.
525-530
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- Lee Calcraft, Rod Adams, Neil Davey:
Sparsely-connected associative memory models with displaced connectivity.
531-536
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- Alexander Förster, Alex Graves, Jürgen Schmidhuber:
RNN-based Learning of Compact Maps for Efficient Robot Localization.
537-542
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- Nigel Crook, Wee Jin Goh:
Human motion recognition using Nonlinear Transient Computation.
543-548
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- Leandro M. Almeida, Teresa Bernarda Ludermir:
Automatically searching near-optimal artificial neural networks.
549-554
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- Talles H. Medeiros, Ricardo H. C. Takahashi, Antônio P. Braga:
A new decision strategy in multi-objective training of the artificial neural networks.
555-560
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- Jarkko Ylipaavalniemi, Eerika Savia, Ricardo Vigário, Samuel Kaski:
Functional elements and networks in fMRI.
561-566
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- Liang Wu, Predrag Neskovic:
Feature extraction for EEG classification: representing electrode outputs as a Markov stochastic process.
567-572
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- Xavier Domont, Martin Heckmann, Heiko Wersing, Frank Joublin, Christian Goerick:
A hierarchical model for syllable recognition.
573-578
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- Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, Félix M. Carballal-Fortes, Juan A. Suárez-Romero, Beatriz Pérez-Sánchez:
Classification of computer intrusions using functional networks. A comparative study.
579-584
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- David L. García, Alfredo Vellido, Àngela Nebot:
Identification of churn routes in the Brazilian telecommunications market.
585-590
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Copyright © Sat May 16 23:10:40 2009
by Michael Ley (ley@uni-trier.de)
