Table of Contents

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