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ORCIDESANN 2006: Bruges, Belgium
- 14th European Symposium on Artificial Neural Networks, ESANN 2006, Bruges, Belgium, April 26-28, 2006, Proceedings. 2006
Self-organization, vector quantization and clustering
- Jochen J. Steil, Risto Kõiva, Alessandro Sperduti:
Unsupervised clustering of continuous trajectories of kinematic trees with SOM-SD. 1-6 - Barbara Hammer, Alexander Hasenfuss, Thomas Villmann:
Magnification control for batch neural gas. 7-12 - Lili Zhang, Erzsébet Merényi:
Weighted differential topographic function: a refinement of topographic function. 13-18 - David Meunier, Hélène Paugam-Moisy:
Cluster detection algorithm in neural networks. 19-24 - Enrique Mérida Casermeiro, Domingo López-Rodríguez, Juan Miguel Ortiz-de-Lazcano-Lobato:
Enhanced maxcut clustering with multivalued neural networks and functional annealing. 25-30
Man-Machine-Interfaces - Processing of nervous signals
- Martin Bogdan, Michael Bensch:
Artificial neural networks and machine learning for man-machine-interfaces - processing of nervous signals. 31-40 - Benjamin Schrauwen, Jan M. Van Campenhout:
Linking non-binned spike train kernels to several existing spike train metrics. 41-46 - Ulrich Hoffmann, Jean-Marc Vesin, Touradj Ebrahimi:
Spatial filters for the classification of event-related potentials. 47-52 - Klaus Pawelzik, Udo A. Ernst, David Rotermund:
On-line adaptation of neuro-prostheses with neuronal evaluation signals. 53-58 - Eva Alfaro-Cid, Anna Esparcia-Alcázar, Ken Sharman:
Using distributed genetic programming to evolve classifiers for a brain computer interface. 59-66
Vision and applications
- Monica Bianchini, Ernesto Di Iorio, Marco Maggini, Chiara Mocenni, Augusto Pucci:
A Cyclostationary Neural Network model for the prediction of the NO2 concentration. 67-72 - Alessio Plebe:
Learning Visual Invariance. 73-76
Online Learning in Cognitive Robotics
- Jochen J. Steil, Heiko Wersing:
Recent trends in online learning for cognitive robots. 77-87 - Nicolas Gomond, Jean Marc Salotti:
Extended model of conditioned learning within latent inhibition. 88-94 - Francisco Bellas, José Antonio Becerra, Richard J. Duro:
Construction of a memory management system in an on-line learning mechanism. 95-100 - Michael Götting, Jochen J. Steil, Heiko Wersing, Edgar Körner, Helge J. Ritter:
Adaptive scene-dependent filters in online learning environments. 101-106 - Víctor Uc Cetina:
A multiagent architecture for concurrent reinforcement learning. 107-112 - 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
Learning I
- Ralf Eickhoff, Joaquin Sitte, Ulrich Rückert:
Robust Local Cluster Neural Networks. 119-124 - Kevin A. J. Doherty, Rod Adams, Neil Davey:
Topological Correlation. 125-130 - Mario Nöcker, Fabian Mörchen, Alfred Ultsch:
An algorithm for fast and reliable ESOM learning. 131-136 - Elia Liitiäinen, Nima Reyhani, Amaury Lendasse:
EM-algorithm for training of state-space models with application to time series prediction. 137-142 - Antti Sorjamaa, Amaury Lendasse:
Time series prediction using DirRec strategy. 143-148 - Joseph Rynkiewicz:
Consistent estimation of the architecture of multilayer perceptrons. 149-154 - Yuehui Chen, Bo Yang, Ajith Abraham:
Optimal design of hierarchical wavelet networks for time-series forecasting. 155-160 - Rebecca Steinert, Martin Rehn, Anders Lansner:
Recognition of handwritten digits using sparse codes generated by local feature extraction methods. 161-166 - Jens Teichert, Rainer Malaka:
Iterative context compilation for visual object recognition. 167-172 - Bernard Girau, César Torres-Huitzil:
FPGA implementation of an integrate-and-fire LEGION model for image segmentation. 173-178 - Alexander Gepperth:
Visual object classification by sparse convolutional neural networks. 179-184 - Alexandre Aussem, Pierre Chainais:
Modelling switching dynamics using prediction experts operating on distinct wavelet scales. 185-190 - Sylvain Gelly, Jérémie Mary, Olivier Teytaud:
Learning for stochastic dynamic programming. 191-196 - Tong Boon Tang, Alan F. Murray:
Adaptive Sensor Modelling and Classification using a Continuous Restricted Boltzmann Machine (CRBM). 197-202 - 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 - Sylvain Chevallier, Philippe Tarroux, Hélène Paugam-Moisy:
Saliency extraction with a distributed spiking neural network. 209-214 - Andreas Herzog, Karsten Kube, Bernd Michaelis, Ana D. de Lima, Thomas B. Voigt:
Connection strategies in neocortical networks. 215-220
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 - Amaury Lendasse, Francesco Corona, Jin Hao, Nima Reyhani, Michel Verleysen:
Determination of the Mahalanobis matrix using nonparametric noise estimations. 227-232 - Felipe Alonso Atienza, José Luis Rojo-Álvarez, Gustavo Camps-Valls, Alfredo Rosado Muñoz, Arcadi García-Alberola:
Bootstrap feature selection in support vector machines for ventricular fibrillation detection. 233-238 - Damien François, Vincent Wertz, Michel Verleysen:
The permutation test for feature selection by mutual information. 239-244 - Colin Fyfe, Gayle Leen:
Stochastic Processes for Canonical Correlation Analysis. 245-250
Visualization methods for data mining
- Fabrice Rossi:
Visual Data Mining and Machine Learning. 251-264 - Marc Strickert, Nese Sreenivasulu, Udo Seiffert:
Sanger-driven MDSLocalize - a comparative study for genomic data. 265-270 - Michaël Aupetit:
Visualizing the trustworthiness of a projection. 271-276 - Kadim Tasdemir, Erzsébet Merényi:
Data topology visualization for the Self-Organizing Map. 277-282 - Tomoharu Iwata, Kazumi Saito, Naonori Ueda:
Visual nonlinear discriminant analysis for classifier design. 283-288 - Marian Pena, Colin Fyfe:
Outlier identification with the Harmonic Topographic Mapping. 289-294 - Shadi Al Shehabi, Jean-Charles Lamirel:
A new hyperbolic visualization method for displaying the results of a neural gas model: application to Webometrics. 295-300
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 - Ali Mohammad-Djafari:
Bayesian source separation: beyond PCA and ICA. 313-322 - Rémi Gribonval, Sylvain Lesage:
A survey of Sparse Component Analysis for blind source separation: principles, perspectives, and new challenges. 323-330 - Jorge Igual, Raul Llinares, Andrés Camacho:
Source separation with priors on the power spectrum of the sources. 331-336 - Yannick Deville, Dass Bissessur, Matthieu Puigt, Shahram Hosseini, Hervé Carfantan:
A time-scale correlation-based blind separation method applicable to correlated sources. 337-344 - Alexander Ilin:
Independent dynamics subspace analysis. 345-350 - John Aldo Lee, Frédéric Vrins, Michel Verleysen:
Non-orthogonal Support Width ICA. 351-358 - Nadia Bali, Ali Mohammad-Djafari, Adel Mohammadpour:
Hierarchical markovian models for joint classification, segmentation and data reduction of hyperspectral images. 359-364 - Maciej Pedzisz, Ali Mansour:
A simple idea to separate convolutive mixtures in an undetermined scenario. 365-370 - Aapo Hyvärinen, Urs Köster:
FastISA: A fast fixed-point algorithm for independent subspace analysis. 371-376 - Dinh-Tuan Pham, Frédéric Vrins:
Discriminacy of the minimum range approach to blind separation of bounded sources. 377-382
Learning II
- Vincent Vigneron:
Entropy-based principle and generalized contingency tables. 383-388 - Ignacio Barrio, Enrique Romero, Lluís A. Belanche Muñoz:
On the selection of hidden neurons with heuristic search strategies for approximation. 389-394 - Geoffroy Simon, Michel Verleysen:
Lag selection for regression models using high-dimensional mutual information. 395-400 - 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 - Tomasz Markiewicz, Stanislaw Osowski:
Data mining techniques for feature selection in blood cell recognition. 407-412 - Gayle Leen, Colin Fyfe:
A Gaussian process latent variable model formulation of canonical correlation analysis. 413-418 - Vanessa Gómez-Verdejo, Aníbal R. Figueiras-Vidal:
Designing neural network committees by combining boosting ensembles. 419-424 - Aloísio Carlos de Pina, Gerson Zaverucha:
Using Regression Error Characteristic Curves for Model Selection in Ensembles of Neural Networks. 425-430 - Pete Duell, Iris Fermin, Xin Yao:
Diversity creation in local search for the evolution of neural network ensembles. 431-436 - Nicolás García-Pedrajas, Colin Fyfe:
Immune Network based Ensembles. 437-442 - Rafael del Castillo Gomariz, Nicolás García-Pedrajas:
Classification by means of Evolutionary Response Surfaces. 443-448 - Mikko Multanen, Kimmo Raivio, Pasi Lehtimäki:
Hierarchical analysis of GSM network performance data. 449-454 - Antoine Mahul, Alexandre Aussem:
Learning with monotonicity requirements for optimal routing with end-to-end quality of service constraints. 455-460
Biologically inspired models
- Leena N. Patel, Alan F. Murray, John Hallam:
Evolving multi-segment 'super-lamprey' CPG's for increased swimming control. 461-466 - Nicholas Butko, Jochen Triesch:
Exploring the role of intrinsic plasticity for the learning of sensory representations. 467-472
Kernel methods
- Tuomas Kärnä, Fabrice Rossi, Amaury Lendasse:
LS-SVM functional network for time series prediction. 473-478 - Sándor Szedmák, John Shawe-Taylor:
Synthesis of maximum margin and multiview learning using unlabeled data. 479-484 - Ping Sun, Xin Yao:
Efficient Forward Regression with Marginal Likelihood. 485-490
Nonlinear dynamics
- Tjeerd Olde Scheper, Nigel T. Crook:
Nonlinear dynamics in neural computation. 491-502 - Carlos Lourenço:
Dynamical reservoir properties as network effects. 503-508 - Nigel T. Crook:
Nonlinear transient computation and variable noise tolerance. 509-514 - Roberta Alessio, Laura Cozzi, Vittorio Sanguineti:
Cultures of dissociated neurons display a variety of avalanche behaviours. 515-520
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 - Yi Sun, Mark Robinson, Rod Adams, Rene te Boekhorst, Alistair G. Rust, Neil Davey:
Using sampling methods to improve binding site predictions. 533-538 - Frank-Michael Schleif, Barbara Hammer, Thomas Villmann:
Margin based Active Learning for LVQ Networks. 539-544 - Michael Biehl, Piter Pasma, Marten Pijl, Lidia Sánchez, Nicolai Petkov:
Classification of Boar Sperm Head Images using Learning Vector Quantization. 545-550 - Oleg Okun, Nikolay G. Zagoruiko, Alexessander Alves, Olga Kutnenko, Irina Borisova:
Selection of more than one gene at a time for cancer prediction from gene expression data. 551-556 - Jarkko Venna, Samuel Kaski:
Visualizing gene interaction graphs with local multidimensional scaling. 557-562 - Cornelia Brüß, Felix Bollenbeck, Frank-Michael Schleif, Winfriede Weschke, Thomas Villmann, Udo Seiffert:
Fuzzy image segmentation with Fuzzy Labelled Neural Gas. 563-568 - Minh Quach, Pierre Geurts:
Elucidating the structure of genetic regulatory networks: a study of a second order dynamical model on artificial data. 569-574
Learning III
- Daniel Schneegaß, Thomas Martinetz, Michael Clausohm:
OnlineDoubleMaxMinOver: a simple approximate time and information efficient online Support Vector Classification method. 575-580 - Stefan Klanke, Helge J. Ritter:
Variants of Unsupervised Kernel Regression: General cost functions. 581-586 - Tobias Glasmachers:
Degeneracy in model selection for SVMs with radial Gaussian kernel. 587-592 - Jürgen Schmidhuber, Matteo Gagliolo, Daan Wierstra, Faustino J. Gomez:
Evolino for recurrent support vector machines. 593-598 - Artur J. Ferreira, Mário A. T. Figueiredo:
Hybrid generative/discriminative training of radial basis function networks. 599-604 - Juan José Rodríguez, Jesús Maudes, Carlos J. Alonso:
Rotation-based ensembles of RBF networks. 605-610 - Anthony Mouraud, Hélène Paugam-Moisy:
Learning and discrimination through STDP in a top-down modulated associative memory. 611-616 - Lee Calcraft, Rod Adams, Neil Davey:
Gaussian and exponential architectures in small-world associative memories. 617-622 - Benjamin Schrauwen, Jan M. Van Campenhout:
Parallel hardware implementation of a broad class of spiking neurons using serial arithmetic. 623-628 - Filip Ponulak, Andrzej J. Kasinski:
Generalization properties of spiking neurons trained with ReSuMe method. 629-634 - Marek Barwinski, Rolf P. Würtz:
A sequence-encoding neural network for face recognition. 635-640 - Usman Khan, Abdelaziz Terchi, Sungwoo Lim, David Wright, Sheng Feng Qin:
Freeform surface induction from projected planar curves via neural networks. 641-646 - Andreea Lazar, Gordon Pipa, Jochen Triesch:
The combination of STDP and intrinsic plasticity yields complex dynamics in recurrent spiking networks. 647-652 - Thomas Gabel, Martin A. Riedmiller:
Reducing policy degradation in neuro-dynamic programming. 653-658 - Zahra Hamou Mamar, Pierre Chainais, Alexandre Aussem:
Probabilistic classifiers and time-scale representations: application to the monitoring of a tramway guiding system. 659-664 - 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
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