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ESANN 2007: Bruges, Belgium
- 15th European Symposium on Artificial Neural Networks, ESANN 2007, Bruges, Belgium, April 25-27, 2007, Proceedings. 2007

Dynamic and complex systems
- Thomas Burwick:

Synchronization and acceleration: complementary mechanisms of temporal coding. 1-6 - Wee Jin Goh, Nigel T. 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 de Pádua 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 Tiño:

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 de 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 Abril:

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 - Frédéric Suard, Alain Rakotomamonjy, Abdelaziz Bensrhair:

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 T. 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 Henrique de Medeiros, Ricardo H. C. Takahashi, Antônio de Pádua 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

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