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ORCIDESANN 2008: Bruges, Belgium
- 16th European Symposium on Artificial Neural Networks, ESANN 2008, Bruges, Belgium, April 23-25, 2008, Proceedings. 2008
Dynamical and recurrent systems, control
- Xavier Dutoit, Benjamin Schrauwen, Jan M. Van Campenhout, Dirk Stroobandt, Hendrik Van Brussel, Marnix Nuttin:
Pruning and Regularisation in Reservoir Computing: a First Insight. 1-6 - Guillaume Jouffroy:
Design of Oscillatory Recurrent Neural Network Controllers with Gradient based Algorithms. 7-12 - Duy Nguyen-Tuong, Jan Peters, Matthias W. Seeger, Bernhard Schölkopf:
Learning Inverse Dynamics: a Comparison. 13-18 - Marc Peter Deisenroth, Carl Edward Rasmussen, Jan Peters:
Model-Based Reinforcement Learning with Continuous States and Actions. 19-24
Feature selection, imputation and projection
- Emil Eirola, Elia Liitiäinen, Amaury Lendasse, Francesco Corona, Michel Verleysen:
Using the Delta Test for Variable Selection. 25-30 - Marc Strickert, Frank-Michael Schleif
, Thomas Villmann:
Metric adaptation for supervised attribute rating. 31-36 - Pedro J. García-Laencina, José-Luis Sancho-Gómez, Aníbal R. Figueiras-Vidal, Michel Verleysen:
K-nearest neighbours based on mutual information for incomplete data classification. 37-42 - Victor Onclinx, Vincent Wertz, Michel Verleysen:
Nonlinear data projection on a sphere with controlled trade-off between trustworthiness and continuity. 43-48 - John Aldo Lee, Michel Verleysen:
Rank-based quality assessment of nonlinear dimensionality reduction. 49-54
Machine learning methods in cancer research
- Alfredo Vellido, Elia Biganzoli, Paulo J. G. Lisboa:
Machine learning in cancer research: implications for personalised medicine. 55-64 - Ben Van Calster, Dirk Timmerman, Antonia C. Testa, Lil Valentin, Sabine Van Huffel:
Multi-class classification of ovarian tumors. 65-70 - René Natowicz, Antônio de Pádua Braga, Roberto Incitti, Euler G. Horta, Roman Rouzier, Thiago S. Rodrigues, Marcelo Azevedo Costa:
A new method of DNA probes selection and its use with multi-objective neural network for predicting the outcome of breast cancer preoperative chemotherapy. 71-76 - Félix Fernando González-Navarro, Lluís A. Belanche Muñoz:
Feature Selection in Proton Magnetic Resonance Spectroscopy for Brain Tumor Classification. 77-82 - Annalisa Barla, Sofia Mosci, Lorenzo Rosasco, Alessandro Verri:
A method for robust variable selection with significance assessment. 83-88 - Vanya Van Belle, Kristiaan Pelckmans, Johan A. K. Suykens, Sabine Van Huffel:
Survival SVM: a practical scalable algorithm. 89-94 - Enrique Romero, Margarida Julià-Sapé, Alfredo Vellido:
DSS-oriented exploration of a multi-centre magnetic resonance spectroscopy brain tumour dataset through visualization. 95-100 - Sergio Rodrigues de Morais, Alexandre Aussem, Marilys Corbex:
Handling almost-deterministic relationships in constraint-based Bayesian network discovery : Application to cancer risk factor identification. 101-106
Learning I
- Lee Calcraft, Rod Adams, Weiliang Chen, Neil Davey:
Using graph-theoretic measures to predict the performance of associative memory models. 107-112 - Rama Murthy Garimella, Praveen Dasigi:
A novel autoassociative memory on the complex hypercubic lattice. 113-118 - Zöhre Kara Kayikci, Günther Palm:
Word recognition and incremental learning based on neural associative memories and hidden Markov models. 119-124 - Huaien Gao, Rudolf Sollacher:
Conditional prediction of time series using spiral recurrent neural network. 125-130 - Alexander Groß, Jan Friedland, Friedhelm Schwenker:
Learning to play Tetris applying reinforcement learning methods. 131-136 - Benoît Frénay, Marco Saerens:
QL2, a simple reinforcement learning scheme for two-player zero-sum Markov games. 137-142 - Alexander Hans, Daniel Schneegaß, Anton Maximilian Schäfer, Steffen Udluft:
Safe exploration for reinforcement learning. 143-148 - Verena Heidrich-Meisner, Christian Igel:
Similarities and differences between policy gradient methods and evolution strategies. 149-154 - Leo Galway, Darryl Charles, Michaela M. Black:
Improvement in Game Agent Control Using State-Action Value Scaling. 155-160 - Víctor Uc Cetina:
Multilayer Perceptrons with Radial Basis Functions as Value Functions in Reinforcement Learning. 161-166 - Jarkko Tikka, Jaakko Hollmén:
Selection of important input variables for RBF network using partial derivatives. 167-172 - Michele La Rocca, Cira Perna:
A multiple testing procedure for input variable selection in neural networks. 173-178 - Alexander Rainer Tassilo Gepperth, Jannik Fritsch, Christian Goerick:
Computationally Efficient Neural Field Dynamics. 179-184
Biological systems and biologically-inspired networks
- Thomas Burwick:
The gamma cycle and its role in the formation of assemblies. 185-190 - Conrad Attard, Andreas Alexander Albrecht:
The impact of axon wiring costs on small neuronal networks. 191-196 - Hooman Shayani, Peter J. Bentley, Andrew M. Tyrrell:
An FPGA-based model suitable for evolution and development of spiking neural networks. 197-202
Clustering and vector quantization
- Markus Hagenbuchner, Alessandro Sperduti, Ah Chung Tsoi:
Self-Organizing Maps for cyclic and unbounded graphs. 203-208 - Hanane Azzag, Mustapha Lebbah:
Clustering of Self-Organizing Map. 209-214 - Lutz Herrmann, Alfred Ultsch:
Explaining Ant-Based Clustering on the basis of Self-Organizing Maps. 215-220 - Aree Witoelar, Anarta Ghosh, Michael Biehl:
Phase transitions in Vector Quantization. 221-226 - Nikolai Alex, Barbara Hammer:
Parallelizing single patch pass clustering. 227-232 - Kai Labusch, Erhardt Barth, Thomas Martinetz:
Learning Data Representations with Sparse Coding Neural Gas. 233-238
Methodology and standards for data analysis with machine learning tools
- Damien François:
Methodology and standards for data analysis with machine learning tools. 239-246 - Yoan Miche, Patrick Bas, Christian Jutten, Olli Simula, Amaury Lendasse:
A Methodology for Building Regression Models using Extreme Learning Machine: OP-ELM. 247-252 - Christiane Lemke, Bogdan Gabrys:
Do we need experts for time series forecasting?. 253-258 - Michaël Aupetit:
Homogeneous bipartition based on multidimensional ranking. 259-264 - Tuomas Alhonnoro, Miki Sirola:
Feature selection on process fault detection and visualization. - Elena Roglia, Rossella Cancelliere, Rosa Meo:
Classification of chestnuts with feature selection by noise resilient classifiers. 271-276 - Alexei Pozdnoukhov, Mikhail F. Kanevski:
GeoKernels: modeling of spatial data on geomanifolds. 277-282
Learning II
- César Ignacio García-Osorio, Nicolás García-Pedrajas:
Constructing ensembles of classifiers using linear projections based on misclassified instances. 283-288 - Bertha Guijarro-Berdiñas, Oscar Fontenla-Romero, Beatriz Pérez-Sánchez, Amparo Alonso-Betanzos:
A Regularized Learning Method for Neural Networks Based on Sensitivity Analysis. 289-294 - David Martínez-Rego, Oscar Fontenla-Romero, Amparo Alonso-Betanzos:
A Method for Time Series Prediction using a Combination of Linear Models. 295-300 - Sebastian Nusser, Clemens Otte, Werner Hauptmann:
Interpretable ensembles of local models for safety-related applications. 301-306 - Mohamed Farouk Abdel Hady, Günther Palm, Friedhelm Schwenker:
Multi-View Forests of Tree-Structured Radial Basis Function Networks Based on Dempster-Shafer Evidence Theory. 307-312 - Fazia Bellal, Khalid Benabdeslem, Alexandre Aussem:
SOM based clustering with instance-level constraints. 313-318 - Alexander Denecke, Heiko Wersing, Jochen J. Steil, Edgar Körner:
Robust object segmentation by adaptive metrics in Generalized LVQ. 319-324 - Alexander Hasenfuss, Barbara Hammer, Tina Geweniger, Thomas Villmann:
Magnification Control in Relational Neural Gas. 325-330 - Marta Kolasa, Rafal Dlugosz:
Parallel asynchronous neighborhood mechanism for WTM Kohonen network implemented in CMOS technology. 331-336 - Tomasz Talaska, Rafal Dlugosz:
Initialization mechanism in Kohonen neural network implemented in CMOS technology. 337-342 - Narayanan Ramanan, Sonia Khatchadourian, Jean-Christophe Prévotet, Lounis Kessal:
Neural network hardware architecture for pattern recognition in the HESS2 project. 343-348 - Massimo De Gregorio:
Active and reactive use of virtual neural sensors. 349-354 - Carlo Casarino, Gaetano Liborio Aiello, Davide Valenti, Bernardo Spagnolo:
Noise influence on correlated activities in a modular neuronal network: from synapses to functional connectivity. 355-360 - Claudio Castellanos Sánchez:
Neuromimetic motion indicator for visual perception. 361-366
Neural Networks for Computational Neuroscience
- David Meunier, Hélène Paugam-Moisy:
Neural networks for computational neuroscience. 367-378 - Frédéric Henry, Emmanuel Daucé:
Emergence of stimulus-specific synchronous response through STDP in recurrent neural networks. 379-384 - Sylvain Chevallier, Philippe Tarroux:
Visual focus with spiking neurons. 385-389 - Andreas Herzog, Karsten Kube, Bernd Michaelis, Ana D. de Lima, Thomas B. Voigt:
Simulation of a recurrent neurointerface with sparse electrical connections. 391-396 - Dominik Brugger, Sergejus Butovas, Martin Bogdan, Cornelius Schwarz, Wolfgang Rosenstiel:
Direct and inverse solution for a stimulus adaptation problem using SVR. 397-402 - Jean Marc Salotti:
Computational model for amygdala neural networks. 403-408
Kernel methods
- Pierre Mahé, Nicola Cancedda:
Factored sequence kernels. 409-414 - Karina Zapien Arreola, Thomas Gärtner, Gilles Gasso, Stéphane Canu:
Regularization path for Ranking SVM. 415-420 - Álvaro Barbero Jiménez, Jorge López Lázaro, José R. Dorronsoro:
An accelerated MDM algorithm for SVM training. 421-426 - Thorsten Suttorp, Christian Igel:
Approximation of Gaussian process regression models after training. 427-432
Machine Learning Approaches and Pattern Recognition for Spectral Data
- Thomas Villmann, Erzsébet Merényi, Udo Seiffert:
Machine learning approches and pattern recognition for spectral data. 433-444 - Fabrice Rossi, Nathalie Villa:
Consistency of Derivative Based Functional Classifiers on Sampled Data. 445-450 - Petra Schneider, Frank-Michael Schleif, Thomas Villmann, Michael Biehl:
Generalized matrix learning vector quantizer for the analysis of spectral data. 451-456 - Amaury Lendasse, Francesco Corona:
Linear Projection based on Noise Variance Estimation - Application to Spectral Data. 457-462 - Caroline Bernard-Michel, Sylvain Douté, Laurent Gardes, Stéphane Girard:
Inverting hyperspectral images with Gaussian Regularized Sliced Inverse Regression. 463-468
Learning III
- Shigeo Abe:
Comparison of sparse least squares support vector regressors trained in primal and dual. 469-474 - Tobias Glasmachers:
On related violating pairs for working set selection in SMO algorithms. 475-480 - Rene te Boekhorst, Irina I. Abnizova, Lorenz Wernisch:
Discrimination of regulatory DNA by SVM on the basis of over- and under-represented motifs. 481-486 - Laura Diosan, Alexandrina Rogozan, Jean-Pierre Pécuchet:
Automatic alignment of medical vs. general terminologies. 487-492 - Zhang Yuecheng, Andriy Mnih, Geoffrey E. Hinton:
Improving a statistical language model by modulating the effects of context words. 493-498 - Soufiane El Jelali, Abdelouahid Lyhyaoui, Aníbal R. Figueiras-Vidal:
An emphasized target smoothing procedure to improve MLP classifiers performance. 499-504 - Mauricio Cerda, Bernard Girau:
A neural model with feedback for robust disambiguation of motion. 505-510 - Carlos Spínola, Carlos J. Gálvez-Fernández, José Muñoz-Pérez, José M. Bonelo, Javier Ferrer, Julio Vizoso:
Multilayer perceptron to model the decarburization process in stainless steel production. 511-516 - Guido Vagliasindi, Paolo Arena, Luigi Fortuna, Andrea Murari, Giuseppe Mazzitelli, Antonio Gallo, Umberto Vagliasindi:
An automatic identifier of Confinement Regimes at JET combining Fuzzy Logic and Classification Trees. 517-522 - Wolfram Schenck, Dennis Sinder, Ralf Möller:
Combining neural networks and optimization techniques for visuokinesthetic prediction and motor planning. 523-528 - Edouard Leclercq, Souleiman Ould el Medhi, Dimitri Lefebvre:
Petri nets design based on neural networks. 529-534 - Ludwig Lausser, Friedhelm Schwenker, Günther Palm:
Detecting zebra crossings utilizing AdaBoost. 535-540
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