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ESANN 2010: Bruges, Belgium
- 18th European Symposium on Artificial Neural Networks, ESANN 2010, Bruges, Belgium, April 28-30, 2010, Proceedings. 2010
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 J. 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 K. 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. - Lahouari Ghouti, 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 C. 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
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 A. Riedmiller:
Deep learning of visual control policies. - Dietlind Zühlke, Frank-Michael Schleif
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 B. 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 David Martín-Guerrero:
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 David Martín-Guerrero, 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 Reyes:
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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