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ESANN 2012: Bruges, Belgium
- 20th European Symposium on Artificial Neural Networks, ESANN 2012, Bruges, Belgium, April 25-27, 2012. 2012
Theory and practice of adaptive input driven dynamical dystems
- Manjunath Gandhi, Peter Tiño, Herbert Jaeger:
Theory of Input Driven Dynamical Systems. - José Manuel Gutiérrez, Daniel San-Martín, Silvia Ortin, Luis Pesquera:
Simple reservoirs with chain topology based on a single time-delay nonlinear node. - Christian Emmerich, René Felix Reinhart, Jochen J. Steil:
Balancing of neural contributions for multi-modal hidden state association. - Davide Bacciu, Alessio Micheli, Alessandro Sperduti:
Input-Output Hidden Markov Models for trees. - Claudio Gallicchio, Alessio Micheli, Giulio Visco:
Constructive Reservoir Computation with Output Feedbacks for Structured Domains. - Phil Weber, Peter Tiño, Behzad Bordbar:
Process Mining in Non-Stationary Environments. - Peter Tiño, Ali Rodan:
Short Term Memory Quantifications in Input-Driven Linear Dynamical Systems.
Regression
- Alejandro Marcos Alvarez, Francis Maes, Louis Wehenkel:
Supervised learning to tune simulated annealing for in silico protein structure prediction. - Davide Anguita, Alessandro Ghio, Luca Oneto, Sandro Ridella:
Structural Risk Minimization and Rademacher Complexity for Regression. - Joseph Rynkiewicz, Solohaja-Faniaha Dimby:
Quantile regression with multilayer perceptrons. - Marc Strickert, Michael Seifert:
Posterior regularization and attribute assessment of under-determined linear mappings. - Frank-Florian Steege, Volker Stephan, Horst-Michael Groß:
Effects of noise-reduction on neural function approximation. - David Picard, Nicolas Thome, Matthieu Cord, Alain Rakotomamonjy:
Learning geometric combinations of Gaussian kernels with alternating Quasi-Newton algorithm. - Audrey Robinel, Didier Puzenat:
Real time drunkenness analysis in a realistic car simulation. - Ananda Freire, Andre Lemme, Jochen J. Steil, Guilherme A. Barreto:
Learning visuo-motor coordination for pointing without depth calculation.
Brain-computer interfaces
- Alexandre Barachant, Stéphane Bonnet, Marco Congedo, Christian Jutten:
BCI Signal Classification using a Riemannian-based kernel. - Martin Spüler, Wolfgang Rosenstiel, Martin Bogdan:
One Class SVM and Canonical Correlation Analysis increase performance in a c-VEP based Brain-Computer Interface (BCI). - Yuan Yang, Sylvain Chevallier, Joe Wiart, Isabelle Bloch:
Automatic selection of the number of spatial filters for motor-imagery BCI. - Sandra Rousseau, Christian Jutten, Marco Congedo:
The error-related potential and BCIs. - Hannes Riechmann, Andrea Finke:
Semi-Supervised Neural Gas for Adaptive Brain-Computer Interfaces.
Image and time series analysis
- Laurent Sifre, Stéphane Mallat:
Combined scattering for rotation invariant texture analysis. - Madalina Olteanu, James Ridgway:
Hidden Markov models for time series of counts with excess zeros. - Mohammad Niknazar, Bertrand Rivet, Christian Jutten:
Application of Dynamic Time Warping on Kalman Filtering Framework for Abnormal ECG Filtering. - Carlos Wilson Dantas de Almeida, Renata M. C. R. Souza, Ana Lucia B. Candeias:
texture classification based on symbolic data analysis. - Hannes Schulz, Sven Behnke:
Learning Object-Class Segmentation with Convolutional Neural Networks. - Guillaume Bernard, Michel Verleysen, John Aldo Lee:
Incremental feature building and classification for image segmentation.
Interpretable models in machine learning
- Alfredo Vellido, José David Martín-Guerrero, Paulo J. G. Lisboa:
Making machine learning models interpretable. - Vanya Van Belle, Sabine Van Huffel, Johan A. K. Suykens, Stephen P. Boyd:
Interval coded scoring systems for survival analysis. - Bassam Mokbel, Wouter Lueks, Andrej Gisbrecht, Michael Biehl, Barbara Hammer:
Visualizing the quality of dimensionality reduction. - Thomas Villmann, Erzsébet Merényi, William H. Farrand:
Unmixing Hyperspectral Images with Fuzzy Supervised Self-Organizing Maps. - Héctor Ruiz, Sandra Ortega-Martorell, Ian H. Jarman, José David Martín-Guerrero, Paulo J. G. Lisboa:
Constructing similarity networks using the Fisher information metric. - José María Martínez-Martínez, Pablo Escandell-Montero, Emilio Soria-Olivas, José David Martín-Guerrero, Juan Gómez-Sanchís, Joan Vila-Francés:
extended visualization method for classification trees. - Alessandra Tosi, Alfredo Vellido:
Cartogram representation of the batch-SOM magnification factor. - Marika Kästner, Wieland Hermann, Thomas Villmann:
Integration of Structural Expert Knowledge about Classes for Classification Using the Fuzzy Supervised Neural Gas. - Lluís Belanche, Jerónimo Hernández-González:
Similarity networks for heterogeneous data. - Grzegorz Zycinski, Margherita Squillario, Annalisa Barla, Tiziana Sanavia, Alessandro Verri, Barbara Di Camillo:
Discriminant functional gene groups identification with machine learning and prior knowledge.
Machine ensembles: theory and applications
- Aníbal R. Figueiras-Vidal, Lior Rokach:
An Exploration of Research Directions in Machine Ensemble Theory and Applications. - Daniel Hernández-Lobato, Gonzalo Martínez-Muñoz, Alberto Suárez:
On the Independence of the Individual Predictions in Parallel Randomized Ensembles. - Lena Chekina, Lior Rokach, Bracha Shapira:
Introducing diversity among the models of multi-label classification ensemble. - Zaid J. Towfic, Jianshu Chen, Ali H. Sayed:
Distributed learning via Diffusion adaptation with application to ensemble learning. - Pablo Escandell-Montero, José María Martínez-Martínez, Emilio Soria-Olivas, Josep Guimerá-Tomás, Marcelino Martínez-Sober, Antonio J. Serrano-López:
Regularized Committee of Extreme Learning Machine for Regression Problems. - Alexis Lechervy, Philippe Henri Gosselin, Frédéric Precioso:
Linear kernel combination using boosting. - Jérôme Paul, Michel Verleysen, Pierre Dupont:
The stability of feature selection and class prediction from ensemble tree classifiers.
Bayesian and graphical models, optimization
- Ali Faisal, Jussi Gillberg, Jaakko Peltonen, Gayle Leen, Samuel Kaski:
Sparse Nonparametric Topic Model for Transfer Learning. - Alberto Testolin, Alessandro Sperduti, Ivilin Peev Stoianov, Marco Zorzi:
Assessment of sequential Boltmann machines on a lexical processing task. - Faicel Chamroukhi, Hervé Glotin, Céline Rabouy:
Functional Mixture Discriminant Analysis with hidden process regression for curve classification. - Nan Wang, Jan Melchior, Laurenz Wiskott:
An analysis of Gaussian-binary restricted Boltzmann machines for natural images. - Marcel Hermkes, Nicolas Kuehn, Carsten Riggelsen:
learning task relatedness via dirichlet process priors for linear regression models. - Jan Steckel, Andre Boen, Dieter Vanderelst, Herbert Peremans:
EMFit based Ultrasonic Phased Arrays with evolved Weights for Biomimetic Target Localization.
Unsupervised learning
- Enrique Pelayo, J. David Buldain Pérez, Carlos Orrite:
magnitude sensitive competitive learning. - Anthony Mouraud, Quentin Barthélemy, Aurélien Mayoue, Cédric Gouy-Pailler, Anthony Larue, Hélène Paugam-Moisy:
From neuronal cost-based metrics towards sparse coded signals classification. - Mark J. Embrechts, Jonathan D. Linton, Christopher J. Gatti:
Hybrid hierarchical clustering: cluster assessment via cluster validation indices. - Thomas Guthier, Julian Eggert, Volker Willert:
Unsupervised learning of motion patterns. - Anastasios Bellas, Charles Bouveyron, Marie Cottrell, Jérôme Lacaille:
Robust clustering of high-dimensional data. - Manel Jouini, Sylvie Thiria, Michel Crépon:
Image reconstruction using an iterative SOM based algorithm.
Statistical methods and kernel-based algorithms
- Kris De Brabanter, Bart De Moor:
Deconvolution in nonparametric statistics. - Philippe Dreesen, Kim Batselier, Bart De Moor:
Weighted/Structured Total Least Squares problems and polynomial system solving. - Dries Geebelen, Kim Batselier, Philippe Dreesen, Marco Signoretto, Johan A. K. Suykens, Bart De Moor, Joos Vandewalle:
Joint Regression and Linear Combination of Time Series for Optimal Prediction. - Lluís Belanche, Alessandra Tosi:
Averaging of kernel functions. - Kim Batselier, Philippe Dreesen, Bart De Moor:
maximum likelihood estimation and polynomial system solving.
Classification and model selection
- Arnaud Joly, François Schnitzler, Pierre Geurts, Louis Wehenkel:
L1-based compression of random forest models. - Gaurav Maheshwari, Vikram Pudi:
RNN Based Batch Mode Active Learning Framework. - Kerstin Bunte, Frank-Michael Schleif
, Michael Biehl:
Adaptive learning for complex-valued data. - Amine Chaibi, Hanane Azzag, Mustapha Lebbah:
Automatic Group-Outlier Detection. - Nicolas Cheifetz, Allou Samé, Patrice Aknin, Emmanuel De Verdalle:
A CUSUM approach for online change-point detection on curve sequences. - David Martínez-Rego, Evan Kriminger, José C. Príncipe, Oscar Fontenla-Romero, Amparo Alonso-Betanzos:
One-class classifier based on extreme value statistics. - Andreas Backhaus, Praveen Cheriyan Ashok, Bavishna Balagopal Praveen, Kishan Dholakia, Udo Seiffert:
Classifying Scotch Whisky from near-infrared Raman spectra with a Radial Basis Function Network with Relevance Learning. - Dorra Trabelsi, Samer Mohammed, Faicel Chamroukhi, Latifa Oukhellou, Yacine Amirat:
Supervised and unsupervised classification approaches for human activity recognition using body-mounted sensors. - Michael Biehl, Petra Schneider, David Smith, Han Stiekema, Angela Taylor, Beverly Hughes, Cedric Shackleton, Paul Stewart, Wiebke Arlt:
Matrix relevance LVQ in steroid metabolomics based classification of adrenal tumors. - Caio Souza, Flavio Nobre, Priscila M. V. Lima, Robson Silva, Rodrigo Brindeiro, Felipe M. G. França:
Recognition of HIV-1 subtypes and antiretroviral drug resistance using weightless neural networks. - Alessandro Rudi, Gabriele Chiusano, Alessandro Verri:
Adaptive Optimization for Cross Validation. - Davide Anguita, Luca Ghelardoni, Alessandro Ghio, Luca Oneto, Sandro Ridella:
The 'K' in K-fold Cross Validation.
Recent developments in clustering algorithms
- Charles Bouveyron, Barbara Hammer, Thomas Villmann:
Recent developments in clustering algorithms. - Julien Jacques, Cristian Preda:
Curves clustering with approximation of the density of functional random variables. - Tina Geweniger, Marika Kästner, Mandy Lange, Thomas Villmann:
Modified Conn-Index for the evaluation of fuzzy clusterings. - Mohamed Khalil El Mahrsi, Fabrice Rossi:
modularity-based clustering for network-constrained trajectories. - Matthieu Durut, Benoît Patra, Fabrice Rossi:
A Discussion on Parallelization Schemes for Stochastic Vector Quantization Algorithms. - Brieuc Conan-Guez, Fabrice Rossi:
Dissimilarity Clustering by Hierarchical Multi-Level Refinement. - Andrej Gisbrecht, Dusan Sovilj, Barbara Hammer, Amaury Lendasse:
Relevance learning for time series inspection.
Feature selection and information-based learning
- Lubomir Kostal, Petr Lánský, Ondrej Pokora:
How regular is neuronal activity? - Benoît Frénay, Gauthier Doquire, Michel Verleysen:
On the Potential Inadequacy of Mutual Information for Feature Selection. - Frederico Coelho, Antônio de Pádua Braga, Michel Verleysen:
Cluster homogeneity as a semi-supervised principle for feature selection using mutual information. - Hela Daassi-Gnaba, Yacine Oussar:
enhanced emotion recognition by feature selection to animate a talking head. - Suviseshamuthu Easter Selvan, Amit Chattopadhyay, Umberto Amato, Pierre-Antoine Absil:
Range-based non-orthogonal ICA using cross-entropy method.
Nonlinear dimensionality reduction and topological learning
- John Aldo Lee:
Type 1 and 2 symmetric divergences for stochastic neighbor embedding. - Andrej Gisbrecht, Wouter Lueks, Bassam Mokbel, Barbara Hammer:
Out-of-sample kernel extensions for nonparametric dimensionality reduction. - Maxime Maillot, Michaël Aupetit, Gérard Govaert:
A generative model that learns Betti numbers from a data set.
Recurrent and neural networks, reinforcement learning, control
- Ben McElroy, Michael Gillham, Gareth Howells, Sarah K. Spurgeon, Stephen Kelly, John C. Batchelor, Matthew Pepper:
Highly efficient localisation utilising weightless neural systems. - Bernard Manderick, Saba Q. Yahyaa:
The Exploration vs Exploitation Trade-Off in Bandit Problems: An Empirical Study. - Klaus Neumann, Jochen J. Steil:
intrinsic plasticity via natural gradient descent. - Alexey Minin, Alois C. Knoll, Hans-Georg Zimmermann:
Complex Valued Artificial Recurrent Neural Network as a Novel Approach to Model the Perceptual Binding Problem. - Tim Waegeman, Francis Wyffels, Benjamin Schrauwen:
A discrete/rhythmic pattern generating RNN. - Hugo Martin, Sylvain Chevallier, Éric Monacelli:
Fast calibration of hand movements-based interface for arm exoskeleton control. - Hunor Jakab, Lehel Csató:
Manifold-based non-parametric learning of action-value functions. - Siegmund Duell, Lina Weichbrodt, Alexander Hans, Steffen Udluft:
Recurrent Neural State Estimation in Domains with Long-Term Dependencies. - Thierry Viéville, Rodrigo Salas, Bruno Cessac:
Using event-based metric for event-based neural network weight adjustment.
Parallel hardware architectures for acceleration of neural network computation
- Ulrich Rückert, Erzsébet Merényi:
Parallel neural hardware: the time is right. - Sebastian Millner, Andreas Hartel, Johannes Schemmel, Karlheinz Meier:
Towards biologically realistic multi-compartment neuron model emulation in analog VLSI. - Peter Wittek, Sándor Darányi:
A GPU-accelerated algorithm for self-organizing maps in a distributed environment. - Rafal Dlugosz, Tomasz Talaska, Witold Pedrycz, Pierre-André Farine:
Low-Power Manhattan Distance Calculation Circuit for Self-Organizing Neural Networks Implemented in the CMOS Technology. - Michele De Filippo De Grazia, Ivilin Peev Stoianov, Marco Zorzi:
Parallelization of Deep Networks. - Andreas Backhaus, Jan Lachmair, Ulrich Rückert, Udo Seiffert:
Hardware accelerated real time classification of hyperspectral imaging data for coffee sorting. - Rafal Dlugosz, Marta Kolasa, Michal Szulc, Witold Pedrycz, Pierre-André Farine:
Implementation Issues of Kohonen Self-Organizing Map Realized on FPGA. - Arne Heittmann, Tobias G. Noll:
A hybrid CMOS/memristive nanoelectronic circuit for programming synaptic weights. - Jan Lachmair, Erzsébet Merényi, Mario Porrmann, Ulrich Rückert:
gNBXe - a Reconfigurable Neuroprocessor for Various Types of Self-Organizing Maps.
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