ESANN 2008: Bruges, Belgium
ESANN 2008, 16th European Symposium on Artificial Neural Networks, 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 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
- Victor 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 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
- Lutz Herrmann, Alfred Ultsch: Explaining Ant-Based Clustering on the basis of Self-Organizing Maps. 215-220
- 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
- Michaël Aupetit: Homogeneous bipartition based on multidimensional ranking. 259-264
- 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
- Cesar 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
- Frédéric Henry, Emmanuel Daucé: Emergence of stimulus-specific synchronous response through STDP in recurrent neural networks. 379-384
- 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
- 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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last updated on 2013-06-18T211851 by the dblp team