ESANN 2010: Bruges, Belgium

Supervised and recurrent models

• Andre Lemme, René Felix Reinhart, Jochen Jakob Steil:
  Efficient online learning of a non-negative sparse autoencoder.
  
• Siegmund Duell, Alexander Hans, Steffen Udluft:
  The Markov Decision Process Extraction Network.
  
• Davide Anguita, Alessandro Ghio, Sandro Ridella:
  Maximal Discrepancy for Support Vector Machines.
  
• Yoan Miche, Emil Eirola, Patrick Bas, Olli Simula, Christian Jutten, Amaury Lendasse, Michel Verleysen:
  Ensemble Modeling with a Constrained Linear System of Leave-One-Out Outputs.
  
• Bjoern Krollner, Bruce J. Vanstone, Gavin R. Finnie:
  Financial time series forecasting with machine learning techniques: a survey.
  

Computational Intelligence Business Applications

• Thiago Turchetti Maia, Antônio de Pádua Braga:
  Introduction to Computational Intelligence Business Applications.
  
• Andrea Burattin, Alessandro Sperduti:
  Heuristics Miner for Time Intervals.
  
• Mikhail F. Kanevski, Vadim Timonin:
  Machine learning analysis and modeling of interest rate curves.
  
• Mauro Mazzieri, Sara Topi, Aldo Franco Dragoni, Germano Vallesi:
  Modeling contextualized textual knowledge as a Long-Term Working Memory.
  

Motion estimation and segmentation

• Jan Steffen, Michael Pardowitz, Jochen Jakob Steil, Helge Ritter:
  Neural competition for motion segmentation.
  
• Volker Willert, Julian Eggert:
  Adaptive velocity tuning for visual motion estimation.
  

Information Visualization, Nonlinear Dimensionality Reduction, Manifold and Topological Learning

• Axel Wismüller, Michel Verleysen, Michaël Aupetit, John Aldo Lee:
  Recent Advances in Nonlinear Dimensionality Reduction, Manifold and Topological Learning.
  
• Jigang Sun, Colin Fyfe, Malcolm Crowe:
  Curvilinear component analysis and Bregman divergences.
  
• Kerstin Bunte, Barbara Hammer, Thomas Villmann, Michael Biehl, Axel Wismüller:
  Exploratory Observation Machine (XOM) with Kullback-Leibler Divergence for Dimensionality Reduction and Visualization.
  
• Marc Strickert, Axel J. Soto, Gustavo E. Vazquez:
  Adaptive matrix distances aiming at optimum regression subspaces.
  
• Etienne Côme, Marie Cottrell, Michel Verleysen, Jérôme Lacaille:
  Self Organizing Star (SOS) for health monitoring.
  
• Elina Parviainen:
  Reliability of dimension reduction visualizations of hierarchical structures.
  
• Sylvain Lespinats, Michaël Aupetit:
  Mapping without visualizing local default is nonsense.
  

Learning I

• Shigeo Abe:
  Active set training of support vector regressors.
  
• Loris Foresti, Devis Tuia, Vadim Timonin, Mikhail F. Kanevski:
  Time series input selection using multiple kernel learning.
  
• Dietmar Bauer, Jonas Sjöberg:
  Fast and good initialization of RBF networks.
  
• Jorge López Lázaro, José R. Dorronsoro:
  Least 1-Norm SVMs: a new SVM variant between standard and LS-SVMs.
  
• Mark J. Embrechts, Blake J. Hargis, Jonathan D. Linton:
  An augmented efficient backpropagation training strategy for deep autoassociative neural networks.
  
• Pierre Lorrentz, Gareth Howells, Klaus D. McDonald-Maier:
  Model Learning from Weights by Adaptive Enhanced Probabilistic Convergent Network.
  
• Dieter Devlaminck, Willem Waegeman, Bruno Bauwens, Bart Wyns, Georges Otte, Luc Boullart, Patrick Santens:
  Directional predictions for 4-class BCI data.
  
• Zoltán Szabó:
  Autoregressive independent process analysis with missing observations.
  
• Ilaria Bertini, Matteo De Felice, Stefano Pizzuti:
  Combining back-propagation and genetic algorithms to train neural networks for start-up time modeling in combined cycle power plants.
  
• Soufiane El Jelali, Abdelouahid Lyhyaoui, Aníbal R. Figueiras-Vidal:
  A pseudoregression formulation of emphasized soft target procedures for classification problems.
  
• Chen Zhang, Julian Eggert:
  Exploiting hierarchical prediction structures for mixed 2d-3d tracking.
  
• Ghouti Lahouari, Saeed Al-Bukhitan:
  Hybrid Soft Computing for PVT Properties Prediction.
  
• Lars Frank Große, Franz Joos:
  Approximation of chemical reaction rates in turbulent combustion simulation.
  

Mixture and generative models

• Hannes Schulz, Andreas Müller, Sven Behnke:
  Exploiting local structure in stacked Boltzmann machines.
  
• Madalina Olteanu, Joseph Rynkiewicz:
  Asymptotic properties of mixture-of-experts models.
  
• Wolfram Schenck, Ralph Welsch, Alexander Kaiser, Ralf Möller:
  Adaptive learning rate control for "neural gas principal component analysis".
  
• François Schnitzler, Philippe Leray, Louis Wehenkel:
  Towards sub-quadratic learning of probability density models in the form of mixtures of trees.
  

Sparse representation of data

• Thomas Villmann, Frank-Michael Schleif, Barbara Hammer:
  Sparse representation of data.
  
• Carlos Alzate, Johan A. K. Suykens:
  Highly sparse kernel spectral clustering with predictive out-of-sample extensions.
  
• Kai Labusch, Thomas Martinetz:
  Learning sparse codes for image reconstruction.
  
• Ernest Mwebaze, Petra Schneider, Frank-Michael Schleif, Sven Haase, Thomas Villmann, Michael Biehl:
  Divergence based Learning Vector Quantization.
  
• Daniel Dornbusch, Robert Haschke, Stefan Menzel, Heiko Wersing:
  Finding correlations in multimodal data using decomposition approaches.
  
• Joan Bruna, Stéphane Mallat:
  Geometric models with co-occurrence groups.
  
• Sascha Lange, Martin Riedmiller:
  Deep learning of visual control policies.
  
• Dietlind Zühlke, Frank-Michael Schleif, Tina Geweniger, Sven Haase, Thomas Villmann:
  Learning vector quantization for heterogeneous structured data.
  
• Andrej Gisbrecht, Bassam Mokbel, Barbara Hammer:
  Relational Generative Topographic Map.
  

Physiology and learning

• Thomas Burwick:
  Neural oscillations allow for selective inhibition - New perspective on the role of cortical gamma oscillations.
  
• Annalisa Barla, Luca Baldassarre, Nicoletta Noceti, Francesca Odone:
  Learning how to grasp objects.
  

Machine learning techniques based on random projections

• Yoan Miche, Benjamin Schrauwen, Amaury Lendasse:
  Machine Learning Techniques based on Random Projections.
  
• John Butcher, David Verstraeten, Benjamin Schrauwen, Charles Day, Peter Haycock:
  Extending reservoir computing with random static projections: a hybrid between extreme learning and RC.
  
• Mark van Heeswijk, Yoan Miche, Erkki Oja, Amaury Lendasse:
  Solving Large Regression Problems using an Ensemble of GPU-accelerated ELMs.
  
• Benoît Frénay, Michel Verleysen:
  Using SVMs with randomised feature spaces: an extreme learning approach.
  
• Claudio Gallicchio, Alessio Micheli:
  A Markovian characterization of redundancy in echo state networks by PCA.
  
• Yuan Lan, Yeng Chai Soh, Guang-Bin Huang:
  Random search enhancement of error minimized extreme learning machine.
  
• Claudio Gallicchio, Alessio Micheli:
  TreeESN: a Preliminary Experimental Analysis.
  

Learning II

• George McConnon, Farzin Deravi, Sanaul Hoque, Gareth Howells, Konstantinos Sirlantzis:
  A novel interactive biometric passport photograph alignment system.
  
• Pierre B. Borckmans, Pierre-Antoine Absil:
  Oriented Bounding Box Computation Using Particle Swarm Optimization.
  
• Tian Lan, Deniz Erdogmus, Lois M. Black, Jan P. H. van Santen:
  Identifying informative features for ERP speller systems based on RSVP paradigm.
  
• Karim El-Laithy, Martin Bogdan:
  Predicting spike-timing of a thalamic neuron using a stochastic synaptic model.
  
• Ioana Sporea, André Grüning:
  Modelling the McGurk effect.
  
• Christian Mayr, Johannes Partzsch, René Schüffny:
  A critique of BCM behavior verification for STDP-type plasticity models.
  

Unsupervised learning

• Kadim Tasdemir, Pavel Milenov:
  An automated SOM clustering based on data topology.
  
• Nicola Rebagliati, Alessandro Verri:
  A randomized algorithm for spectral clustering.
  
• Andrej Gisbrecht, Barbara Hammer:
  Relevance learning in generative topographic maps.
  
• Luís Gustavo M. Souza, Guilherme De A. Barreto:
  Multiple Local Models for System Identification Using Vector Quantization Algorithms.
  
• Tina Geweniger, Thomas Villmann:
  Extending FSNPC to handle data points with fuzzy class assignments.
  

Image and video analysis

• Erhan Bas, Deniz Erdogmus:
  Principal curve tracing.
  
• Arnaud de Decker, John Aldo Lee, Damien François, Michel Verleysen:
  Mode estimation in high-dimensional spaces with flat-top kernels: application to image denoising.
  
• Alexander Denecke, Irene Ayllón Clemente, Heiko Wersing, Julian Eggert, Jochen Jakob Steil:
  Figure-ground Segmentation using Metrics Adaptation in Level Set Methods.
  
• Rafael Marcos Luque, Enrique Domínguez, Esteban J. Palomo, José Muñoz:
  An ART-type network approach for video object detection.
  

Computational Intelligence in Biomedicine

• Paulo J. G. Lisboa, Alfredo Vellido, José D. Martín:
  Computational Intelligence in biomedicine: Some contributions.
  
• Iván Olier, Julià Amengual, Alfredo Vellido:
  Segmentation of EMG time series using a variational Bayesian approach for the robust estimation of cortical silent periods.
  
• Sandra Ortega-Martorell, Iván Olier, Alfredo Vellido, Margarida Julià-Sapé, Carles Arús:
  Spectral Prototype Extraction for dimensionality reduction in brain tumour diagnosis.
  
• Vanya Van Belle, Kristiaan Pelckmans, Johan A. K. Suykens, Sabine Van Huffel:
  On the use of a clinical kernel in survival analysis.
  
• Yi Sun, Gary P. Moss, Maria Prapopoulou, Rod Adams, Marc B. Brown, Neil Davey:
  The Application of Gaussian Processes in the Prediction of Percutaneous Absorption for Mammalian and Synthetic Membranes.
  
• Emilio Soria-Olivas, José D. Martín, Mónica Climente-Martí, Amparo Soldevila, Antonio J. Serrano:
  Neural models for the analysis of kidney disease patients.
  

Learning III

• Alexander Kaiser, Wolfram Schenck, Ralf Möller:
  Distance functions for local PCA methods.
  
• Mabel González Castellanos, Yanet Rodríguez Sarabia, Carlos Morell:
  KNN behavior with set-valued attributes.
  
• Iván Olier, Alfredo Vellido, Jesús Giraldo:
  Kernel generative topographic mapping.
  
• Timo Pröscholdt, Michel Crucianu:
  On Finding Complementary Clusterings.
  
• Haytham Elghazel, Khalid Benabdeslem, Fatma Hamdi:
  Consensus clustering by graph based approach.
  
• Esteban J. Palomo, Enrique Domínguez, Rafael Marcos Luque, José Muñoz:
  Web Document Clustering based on a Hierarchical Self-Organizing Model.
  
• Jean-Louis Gutzwiller, Hervé Frezza-Buet, Olivier Pietquin:
  Online speaker diarization with a size-monitored growing neural gas algorithm.
  
• Andreas Backhaus, Asuka Kuwabara, Andrew Fleming, Udo Seiffert:
  Validation of unsupervised clustering methods for leaf phenotype screening.
  
• Ahmad Ammari, Valentina V. Zharkova:
  A Novel Two-Phase SOM Clustering Approach to Discover Visitor Interests in a Website.
  
• Everardo Maia, Guilherme De A. Barreto, André Luís Vasconcelos Coelho:
  Image registration by the extended evolutionary self-organizing map.
  
• Rafal Dlugosz, Marta Kolasa, Witold Pedrycz:
  Programmable triangular neighborhood functions of Kohonen Self-Organizing Maps realized in CMOS technology.
  
• Ángel Campo, José Santos:
  Evolution of adaptive center-crossing continuous time recurrent neural networks for biped robot control.
  
• Makoto Otsuka, Junichiro Yoshimoto, Kenji Doya:
  Free-energy-based reinforcement learning in a partially observable environment.
  

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