ESANN 2006:
Bruges,
Belgium
ESANN 2006, 14th European Symposium on Artificial Neural Networks, Bruges, Belgium, April 26-28, 2006, Proceedings.
2006 BibTeX
Self-organization,
vector quantization and clustering
Man-Machine-Interfaces - Processing of nervous signals
Vision and applications
Online Learning in Cognitive Robotics
- Jochen J. Steil, Heiko Wersing:
Recent trends in online learning for cognitive robots.
77-87
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- Nicolas Gomond, Jean Marc Salotti:
Extended model of conditioned learning within latent inhibition.
88-94
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- Francisco Bellas, José Antonio Becerra, Richard J. Duro:
Construction of a memory management system in an on-line learning mechanism.
95-100
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- Michael Götting, Jochen J. Steil, Heiko Wersing, Edgar Körner, Helge Ritter:
Adaptive scene-dependent filters in online learning environments.
101-106
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- Victor Uc Cetina:
A multiagent architecture for concurrent reinforcement learning.
107-112
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- Francisco Bellas, José Antonio Becerra, Richard J. Duro:
Some experimental results with a two level memory management system in the multilevel darwinist brain.
113-118
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Learning I
- Ralf Eickhoff, Joaquin Sitte, Ulrich Rückert:
Robust Local Cluster Neural Networks.
119-124
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- Kevin Doherty, Rod Adams, Neil Davey:
Topological Correlation.
125-130
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- Mario Nöcker, Fabian Mörchen, Alfred Ultsch:
An algorithm for fast and reliable ESOM learning.
131-136
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- Elia Liitiäinen, Nima Reyhani, Amaury Lendasse:
EM-algorithm for training of state-space models with application to time series prediction.
137-142
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- Antti Sorjamaa, Amaury Lendasse:
Time series prediction using DirRec strategy.
143-148
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- Joseph Rynkiewicz:
Consistent estimation of the architecture of multilayer perceptrons.
149-154
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- Yuehui Chen, Bo Yang, Ajith Abraham:
Optimal design of hierarchical wavelet networks for time-series forecasting.
155-160
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- Rebecca Steinert, Martin Rehn, Anders Lansner:
Recognition of handwritten digits using sparse codes generated by local feature extraction methods.
161-166
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- Jens Teichert, Rainer Malaka:
Iterative context compilation for visual object recognition.
167-172
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- Bernard Girau, Cesar Torres-Huitzil:
FPGA implementation of an integrate-and-fire LEGION model for image segmentation.
173-178
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- Alexander Gepperth:
Visual object classification by sparse convolutional neural networks.
179-184
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- Alexandre Aussem, Pierre Chainais:
Modelling switching dynamics using prediction experts operating on distinct wavelet scales.
185-190
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- Sylvain Gelly, Jérémie Mary, Olivier Teytaud:
Learning for stochastic dynamic programming.
191-196
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- Tong Boon Tang, Alan F. Murray:
Adaptive Sensor Modelling and Classification using a Continuous Restricted Boltzmann Machine (CRBM).
197-202
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- Mauricio Kugler, Toshiyuki Miyatani, Susumu Kuroyanagi, Anto Satriyo Nugroho, Akira Iwata:
Non-linear gating network for the large scale classification model CombNET-II.
203-208
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- Sylvain Chevallier, Philippe Tarroux, Hélène Paugam-Moisy:
Saliency extraction with a distributed spiking neural network.
209-214
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- Andreas Herzog, Karsten Kube, Bernd Michaelis, Ana D. de Lima, Thomas B. Voigt:
Connection strategies in neocortical networks.
215-220
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Feature extraction and variable projection
- Long Han, Mark J. Embrechts, Boleslaw K. Szymanski, Karsten Sternickel, Alexander Ross:
Random Forests Feature Selection with K-PLS: Detecting Ischemia from Magnetocardiograms.
221-226
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- Amaury Lendasse, Francesco Corona, Jin Hao, Nima Reyhani, Michel Verleysen:
Determination of the Mahalanobis matrix using nonparametric noise estimations.
227-232
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- Felipe Alonso Atienza, José Luis Rojo-Álvarez, Gustavo Camps-Valls, Alfredo Rosado Muñoz, Arcadio García-Alberola:
Bootstrap feature selection in support vector machines for ventricular fibrillation detection.
233-238
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- Damien François, Vincent Wertz, Michel Verleysen:
The permutation test for feature selection by mutual information.
239-244
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- Colin Fyfe, Gayle Leen:
Stochastic Processes for Canonical Correlation Analysis.
245-250
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Visualization methods for data mining
Semi-blind approaches for Source Separation and Independent Component Analysis (ICA)
- Massoud Babaie-Zadeh, Christian Jutten:
Semi-Blind Approaches for Source Separation and Independent component Analysis.
301-312
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- Ali Mohammad-Djafari:
Bayesian source separation: beyond PCA and ICA.
313-322
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- Rémi Gribonval, Sylvain Lesage:
A survey of Sparse Component Analysis for blind source separation: principles, perspectives, and new challenges.
323-330
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- Jorge Igual, Raul Llinares, Andrés Camacho:
Source separation with priors on the power spectrum of the sources.
331-336
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- Yannick Deville, Dass Bissessur, Matthieu Puigt, Shahram Hosseini, Hervé Carfantan:
A time-scale correlation-based blind separation method applicable to correlated sources.
337-344
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- Alexander Ilin:
Independent dynamics subspace analysis.
345-350
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- John Aldo Lee, Frédéric Vrins, Michel Verleysen:
Non-orthogonal Support Width ICA.
351-358
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- Nadia Bali, Ali Mohammad-Djafari, Adel Mohammadpour:
Hierarchical markovian models for joint classification, segmentation and data reduction of hyperspectral images.
359-364
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- Maciej Pedzisz, Ali Mansour:
A simple idea to separate convolutive mixtures in an undetermined scenario.
365-370
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- Aapo Hyvärinen, Urs Köster:
FastISA: A fast fixed-point algorithm for independent subspace analysis.
371-376
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- Dinh-Tuan Pham, Frédéric Vrins:
Discriminacy of the minimum range approach to blind separation of bounded sources.
377-382
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Learning II
- Vincent Vigneron:
Entropy-based principle and generalized contingency tables.
383-388
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- Ignacio Barrio, Enrique Romero, Lluís A. Belanche Muñoz:
On the selection of hidden neurons with heuristic search strategies for approximation.
389-394
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- Geoffroy Simon, Michel Verleysen:
Lag selection for regression models using high-dimensional mutual information.
395-400
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- Terence A. Etchells, Àngela Nebot, Alfredo Vellido, Paulo J. G. Lisboa, Francisco Mugica:
Learning what is important: feature selection and rule extraction in a virtual course.
401-406
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- Tomasz Markiewicz, Stanislaw Osowski:
Data mining techniques for feature selection in blood cell recognition.
407-412
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- Gayle Leen, Colin Fyfe:
A Gaussian process latent variable model formulation of canonical correlation analysis.
413-418
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- Vanessa Gómez-Verdejo, Aníbal R. Figueiras-Vidal:
Designing neural network committees by combining boosting ensembles.
419-424
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- Aloísio Carlos de Pina, Gerson Zaverucha:
Using Regression Error Characteristic Curves for Model Selection in Ensembles of Neural Networks.
425-430
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- Pete Duell, Iris Fermin, Xin Yao:
Diversity creation in local search for the evolution of neural network ensembles.
431-436
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- Nicolás García-Pedrajas, Colin Fyfe:
Immune Network based Ensembles.
437-442
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- Rafael del Castillo Gomariz, Nicolás García-Pedrajas:
Classification by means of Evolutionary Response Surfaces.
443-448
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- Mikko Multanen, Kimmo Raivio, Pasi Lehtimäki:
Hierarchical analysis of GSM network performance data.
449-454
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- Antoine Mahul, Alexandre Aussem:
Learning with monotonicity requirements for optimal routing with end-to-end quality of service constraints.
455-460
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Biologically inspired models
Kernel methods
Nonlinear dynamics
Neural Networks and Machine Learning in Bioinformatics - Theory and Applications
- Udo Seiffert, Barbara Hammer, Samuel Kaski, Thomas Villmann:
Neural networks and machine learning in bioinformatics - theory and applications.
521-532
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- Yi Sun, Mark Robinson, Rod Adams, Rene te Boekhorst, Alistair G. Rust, Neil Davey:
Using sampling methods to improve binding site predictions.
533-538
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- Frank-Michael Schleif, Barbara Hammer, Thomas Villmann:
Margin based Active Learning for LVQ Networks.
539-544
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- Michael Biehl, Piter Pasma, Marten Pijl, Lidia Sánchez, Nicolai Petkov:
Classification of Boar Sperm Head Images using Learning Vector Quantization.
545-550
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- Oleg Okun, Nikolay G. Zagoruiko, Alexessander Alves, Olga Kutnenko, Irina V. Borisova:
Selection of more than one gene at a time for cancer prediction from gene expression data.
551-556
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- Jarkko Venna, Samuel Kaski:
Visualizing gene interaction graphs with local multidimensional scaling.
557-562
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- Cornelia Brüß, Felix Bollenbeck, Frank-Michael Schleif, Winfriede Weschke, Thomas Villmann, Udo Seiffert:
Fuzzy image segmentation with Fuzzy Labelled Neural Gas.
563-568
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- Minh Quach, Pierre Geurts:
Elucidating the structure of genetic regulatory networks: a study of a second order dynamical model on artificial data.
569-574
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Learning III
- Daniel Schneegaß, Thomas Martinetz, Michael Clausohm:
OnlineDoubleMaxMinOver: a simple approximate time and information efficient online Support Vector Classification method.
575-580
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- Stefan Klanke, Helge Ritter:
Variants of Unsupervised Kernel Regression: General cost functions.
581-586
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- Tobias Glasmachers:
Degeneracy in model selection for SVMs with radial Gaussian kernel.
587-592
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- Jürgen Schmidhuber, Matteo Gagliolo, Daan Wierstra, Faustino J. Gomez:
Evolino for recurrent support vector machines.
593-598
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- Artur Ferreira, Mário A. T. Figueiredo:
Hybrid generative/discriminative training of radial basis function networks.
599-604
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- Juan José Rodríguez, Jesús Maudes, Carlos J. Alonso:
Rotation-based ensembles of RBF networks.
605-610
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- Anthony Mouraud, Hélène Paugam-Moisy:
Learning and discrimination through STDP in a top-down modulated associative memory.
611-616
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- Lee Calcraft, Rod Adams, Neil Davey:
Gaussian and exponential architectures in small-world associative memories.
617-622
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- Benjamin Schrauwen, Jan M. Van Campenhout:
Parallel hardware implementation of a broad class of spiking neurons using serial arithmetic.
623-628
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- Filip Ponulak, Andrzej J. Kasinski:
Generalization properties of spiking neurons trained with ReSuMe method.
629-634
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- Marek Barwinski, Rolf P. Würtz:
A sequence-encoding neural network for face recognition.
635-640
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- Usman Khan, Abdelaziz Terchi, Sungwoo Lim, David Wright, Sheng Feng Qin:
Freeform surface induction from projected planar curves via neural networks.
641-646
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- Andreea Lazar, Gordon Pipa, Jochen Triesch:
The combination of STDP and intrinsic plasticity yields complex dynamics in recurrent spiking networks.
647-652
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- Thomas Gabel, Martin Riedmiller:
Reducing policy degradation in neuro-dynamic programming.
653-658
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- Zahra Hamou Mamar, Pierre Chainais, Alexandre Aussem:
Probabilistic classifiers and time-scale representations: application to the monitoring of a tramway guiding system.
659-664
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- Frédéric Ratle, Anne-Laure Terrettaz, Mikhail F. Kanevski, Pierre Esseiva, Olivier Ribaux:
Pattern analysis in illicit heroin seizures: a novel application of machine learning algorithms.
665-670
Electronic Edition (link) BibTeX
Copyright © Sat May 16 23:10:40 2009
by Michael Ley (ley@uni-trier.de)
