ESANN 2007: Bruges, Belgium

Dynamic and complex systems

• Thomas Burwick:
  Synchronization and acceleration: complementary mechanisms of temporal coding. 1-6
  
• Wee Jin Goh, Nigel Crook:
  Pattern Recognition using Chaotic Transients. 7-12
  
• Jan-Hendrik Schleimer, Ricardo Vigário:
  Order in Complex Systems of Nonlinear Oscillators: Phase Locked Subspaces. 13-18
  

Prototype-based learning

• Fabio Aiolli, Giovanni Da San Martino, Alessandro Sperduti, Markus Hagenbuchner:
  "Kernelized" Self-Organizing Maps for Structured Data. 19-24
  
• Fabrice Rossi:
  Model collisions in the dissimilarity SOM. 25-30
  
• Nathalie Villa, Romain Boulet:
  Clustering a medieval social network by SOM using a kernel based distance measure. 31-36
  
• Petra Schneider, Michael Biehl, Barbara Hammer:
  Relevance matrices in LVQ. 37-42
  
• Georges Adrian Drumea, Hervé Frezza-Buet:
  Tracking fast changing non-stationary distributions with a topologically adaptive neural network: application to video tracking. 43-48
  
• Igor Farkas, Matthew W. Crocker:
  Systematicity in sentence processing with a recursive self-organizing neural network. 49-54
  

Model selection and regularization

• Antti Honkela, Jeremias Seppä, Esa Alhoniemi:
  Agglomerative Independent Variable Group Analysis. 55-60
  
• Liang Wu, Predrag Neskovic, Etienne Reyes, Elena Festa, Heindel William:
  Classifying n-back EEG data using entropy and mutual information features. 61-66
  
• Elia Liitiäinen, Francesco Corona, Amaury Lendasse:
  Nearest Neighbor Distributions and Noise Variance Estimation. 67-72
  
• Illya Kokshenev, Antônio P. Braga:
  Complexity bounds of radial basis functions and multi-objective learning. 73-78
  

Fuzzy and Probalistic Methods in Neural Networks and Machine Learning

• Barbara Hammer, Thomas Villmann:
  How to process uncertainty in machine learning?. 79-90
  
• Minoru Nakayama, Yosiyuki Takahasi:
  An Estimation of Response Certainty using Features of Eye-movements. 91-96
  
• Nikolaos Gianniotis, Peter Tino:
  Visualisation of tree-structured data through generative probabilistic modelling. 97-102
  
• Thomas Villmann, Marc Strickert, Cornelia Brüß, Frank-Michael Schleif, Udo Seiffert:
  Visualization of Fuzzy Information in Fuzzy-Classification for Image Segmentation using MDS. 103-108
  

Learning I

• Maite García-Sebastián, Manuel Graña:
  SOM for intensity inhomogeneity correction in MRI. 109-114
  
• Antti Sorjamaa, Paul Merlin, Bertrand Maillet, Amaury Lendasse:
  SOM+EOF for finding missing values. 115-120
  
• Hassan Ghaziri:
  Self-organized chains for clustering. 121-126
  
• Aree Witoelar, Michael Biehl, Anarta Ghosh, Barbara Hammer:
  On the dynamics of Vector Quantization and Neural Gas. 127-132
  
• Alexander Yudashkin:
  Three-dimensional self-organizing dynamical systems for discrete structures memorizing and retrieval. 133-138
  
• Murilo Coelho Naldi, André Carlos Ponce Leon Ferreira de Carvalho:
  Clustering using genetic algorithm combining validation criteria. 139-144
  
• Thomas Girod, Laurent Bougrain, Frédéric Alexandre:
  Toward a robust 2D spatio-temporal self-organization. 145-150
  
• Tomasz Talaska, Rafal Dlugosz, Witold Pedrycz:
  Adaptive Weight Change Mechanism for Kohonens's Neural Network Implemented in CMOS 0.18 um Technology. 151-156
  
• Catherine Krier, Damien François, Fabrice Rossi, Michel Verleysen:
  Feature clustering and mutual information for the selection of variables in spectral data. 157-162
  
• Bernardo Penna Resende de Carvalho, Ricardo de Souza Ribeiro, Talles Henrique de Medeiros:
  Prediction of post-synaptic activity in proteins using recursive feature elimination. 163-168
  
• Piyang Wang, Tommy W. S. Chow:
  A new feature selection scheme using data distribution factor for transactional data. 169-174
  
• Gaetano Liborio Aiello, Carlo Casarino:
  Informational cost in correlation-based neuronal networks. 175-179
  
• Ulrich Rückert, Ralf Eickhoff:
  Controlling complexity of RBF networks by similarity. 181-186
  
• Dirk Gorissen, Wouter Hendrickx, Tom Dhaene:
  Adaptive Global Metamodeling with Neural Networks. 187-192
  

Convex Optimization for the Design of Learning Machines

• Kristiaan Pelckmans, Johan A. K. Suykens, Bart De Moor:
  Convex optimization for the design of learning machines. 193-204
  
• Tijl De Bie:
  Deploying SDP for machine learning. 205-210
  
• Sándor Szedmák, Tijl De Bie, David R. Hardoon:
  A metamorphosis of Canonical Correlation Analysis into multivariate maximum margin learning. 211-216
  
• Gavin C. Cawley:
  Model Selection for Kernel Probit Regression. 217-222
  
• Cecilio Angulo, Davide Anguita, Luis González:
  Interval discriminant analysis using support vector machines. 223-228
  

Generative models and maximum likelihood approaches

• Cédric Archambeau, Nicolas Delannay, Michel Verleysen:
  Mixtures of robust probabilistic principal component analyzers. 229-234
  
• Pierre Gaillard, Michaël Aupetit, Gérard Govaert:
  Learning topology of a labeled data set with the supervised generative gaussian graph. 235-240
  
• Rima Guidara, Shahram Hosseini, Yannick Deville:
  Markovian blind separation of non-stationary temporally correlated sources. 241-246
  
• Nicolas Delannay, Michel Verleysen:
  Collaborative Filtering with interlaced Generalized Linear Models. 247-252
  

Kernel methods and Support Vector Machines

• Gilles Gasso, Karina Zapien Arreola, Stéphane Canu:
  Computing and stopping the solution paths for $\nu$-SVR. 253-258
  
• Shigeo Abe:
  Optimizing kernel parameters by second-order methods. 259-264
  
• Majid Beigi, Andreas Zell:
  A novel kernel-based method for local pattern extraction in random process signals. 265-270
  
• Alain Rakotomamonjy, Manuel Davy:
  One-class SVM regularization path and comparison with alpha seeding. 271-276
  

Reinforcement Learning

• Verena Heidrich-Meisner, Martin Lauer, Christian Igel, Martin A. Riedmiller:
  Reinforcement learning in a nutshell. 277-288
  
• Manuel Loth, Philippe Preux, Manuel Davy:
  A unified view of TD algorithms, introducing Full-gradient TD and Equi-gradient descent TD. 289-294
  
• Jan Peters, Stefan Schaal:
  Applying the Episodic Natural Actor-Critic Architecture to Motor Primitive Learning. 295-300
  
• Daniel Schneegaß, Steffen Udluft, Thomas Martinetz:
  Neural Rewards Regression for near-optimal policy identification in Markovian and partial observable environments. 301-306
  
• Colin Fyfe, Pei Ling Lai:
  Immediate Reward Reinforcement Learning for Projective Kernel Methods. 307-312
  
• Kary Främling:
  Replacing eligibility trace for action-value learning with function approximation. 313-318
  
• Anton Maximilian Schäfer, Steffen Udluft, Hans-Georg Zimmermann:
  The Recurrent Control Neural Network. 319-324
  

Learning II

• Daniel Schneegaß, Anton Maximilian Schäfer, Thomas Martinetz:
  The Intrinsic Recurrent Support Vector Machine. 325-330
  
• Bernardo Penna Resende de Carvalho, Antônio de Pádua Braga:
  A-LSSVM: an Adaline based iterative sparse LS-SVM classifier. 331-336
  
• Daniel Schneegaß, Steffen Udluft, Thomas Martinetz:
  Explicit Kernel Rewards Regression for data-efficient near-optimal policy identification. 337-342
  
• Sumeet Agarwal, V. Vijaya Saradhi, Harish Karnick:
  Kernel-based online machine learning and support vector reduction. 343-348
  
• Zsolt Minier, Lehel Csató:
  Kernel PCA based clustering for inducing features in text categorization. 349-354
  
• Frederic Suard, Alain Rakotomamonjy, Abdelaziz Benrshrair:
  Kernel on Bag of Paths For Measuring Similarity of Shapes. 355-360
  
• Francesc Benimeli, Ken Sharman:
  Electroencephalogram signal classification for brain computer interfaces using wavelets and support vector machines. 361-366
  
• Bertrand Fontaine, Herbert Peremans, Benjamin Schrauwen:
  Bat echolocation modelling using spike kernels with Support Vector Regression. 367-372
  
• Terry Windeatt:
  Ensemble neural classifier design for face recognition. 373-378
  
• J. Salvador Sánchez, Ludmila I. Kuncheva:
  Data reduction using classifier ensembles. 379-384
  
• Patrick Kouontchou, Bertrand Maillet:
  ICA-based High Frequency VaR for Risk Management. 385-390
  
• Travis Wiens, Rich Burton, Greg Schoenau:
  Algebraic inversion of an artificial neural network classifier. 391-396
  
• Karina Zapien Arreola, Gilles Gasso, Stéphane Canu:
  Estimation of tangent planes for neighborhood graph correction. 397-402
  
• Madalina Olteanu, Joseph Rynkiewicz:
  Estimating the Number of Components in a Mixture of Multilayer Perceptrons. 403-408
  

Biologically motivated learning

• Junmei Zhu, Christoph von der Malsburg:
  Derivation of nonlinear amplitude equations for the normal modes of a self-organizing system. 409-414
  
• Jan Wessnitzer, Barbara Webb:
  A neural model of cross-modal association in insects. 415-420
  
• Andreas Herzog, Karsten Kube, Bernd Michaelis, Ana D. de Lima, Thomas B. Voigt:
  Transition from initialization to working stage in biologically realistic networks. 421-426
  
• Hélène Paugam-Moisy, Régis Martinez, Samy Bengio:
  A supervised learning approach based on STDP and polychronization in spiking neuron networks. 427-432
  

Learning causality

• Katerina Hlavácková-Schindler, Pablo F. Verdes:
  Computational Intelligence approaches to causality detection. 433-440
  
• Xiaohai Sun, Dominik Janzing, Bernhard Schölkopf:
  Distinguishing between cause and effect via kernel-based complexity measures for conditional distributions. 441-446
  
• Nikolay V. Manyakov, Marc M. Van Hulle:
  Causality analysis of LFPs in micro-electrode arrays based on mutual information. 447-452
  
• Xiaohai Sun, Dominik Janzing:
  Learning causality by identifying common effects with kernel-based dependence measures. 453-458
  
• Leonardo Angelini, Daniele Marinazzo, Mario Pellicoro, Sebastiano Stramaglia:
  Causality and communities in neural networks. 459-464
  
• Xiaohai Sun, Dominik Janzing:
  Exploring the causal order of binary variables via exponential hierarchies of Markov kernels. 465-470
  

Reservoir Computing

• Benjamin Schrauwen, David Verstraeten, Jan M. Van Campenhout:
  An overview of reservoir computing: theory, applications and implementations. 471-482
  
• Huaien Gao, Rudolf Sollacher, Hans-Peter Kriegel:
  Spiral Recurrent Neural Network for Online Learning. 483-488
  
• Jochen J. Steil:
  Several ways to solve the MSO problem. 489-494
  
• David Verstraeten, Benjamin Schrauwen, Dirk Stroobandt:
  Adapting reservoir states to get Gaussian distributions. 495-500
  
• Carlos Lourenço:
  Structured reservoir computing with spatiotemporal chaotic attractors. 501-506
  
• Xavier Dutoit, Hendrik Van Brussel, Marnix Nuttin:
  A first attempt of reservoir pruning for classification problems. 507-512
  
• Marion Wardermann, Jochen J. Steil:
  Intrinsic plasticity for reservoir learning algorithms. 513-518
  

Learning III

• Eva Kaslik, Stefan Balint:
  Bifurcation analysis for a discrete-time Hopfield neural network of two neurons with two delays. 519-524
  
• José Antonio Gómez-Ruiz, José Muñoz-Pérez, M. Angeles García-Bernal, Ezequiel López-Rubio:
  Spicules-based competitive neural network. 525-530
  
• Lee Calcraft, Rod Adams, Neil Davey:
  Sparsely-connected associative memory models with displaced connectivity. 531-536
  
• Alexander Förster, Alex Graves, Jürgen Schmidhuber:
  RNN-based Learning of Compact Maps for Efficient Robot Localization. 537-542
  
• Nigel Crook, Wee Jin Goh:
  Human motion recognition using Nonlinear Transient Computation. 543-548
  
• Leandro M. Almeida, Teresa Bernarda Ludermir:
  Automatically searching near-optimal artificial neural networks. 549-554
  
• Talles H. Medeiros, Ricardo H. C. Takahashi, Antônio P. Braga:
  A new decision strategy in multi-objective training of the artificial neural networks. 555-560
  
• Jarkko Ylipaavalniemi, Eerika Savia, Ricardo Vigário, Samuel Kaski:
  Functional elements and networks in fMRI. 561-566
  
• Liang Wu, Predrag Neskovic:
  Feature extraction for EEG classification: representing electrode outputs as a Markov stochastic process. 567-572
  
• Xavier Domont, Martin Heckmann, Heiko Wersing, Frank Joublin, Christian Goerick:
  A hierarchical model for syllable recognition. 573-578
  
• Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, Félix M. Carballal-Fortes, Juan A. Suárez-Romero, Beatriz Pérez-Sánchez:
  Classification of computer intrusions using functional networks. A comparative study. 579-584
  
• David L. García, Alfredo Vellido, Àngela Nebot:
  Identification of churn routes in the Brazilian telecommunications market. 585-590