Semi-supervised learning

• 
  Tijl De Bie, Thiago Turchetti Maia, Antônio de Pádua Braga: Machine Learning with Labeled and Unlabeled Data.
• 
  Peng Li, Yiming Ying, Colin Campbell: A Variational Approach to Semi-Supervised Clustering.
• 
  Tuong-Vinh Truong, Massih-Reza Amini, Patrick Gallinari: A self-training method for learning to rank with unlabeled data.
• 
  Kristiaan Pelckmans, Johan A. K. Suykens: Transductively Learning from Positive Examples Only.
• 
  Charles Bouveyron, Stéphane Girard, Madalina Olteanu: Supervised classification of categorical data with uncertain labels for DNA barcoding.
• 
  David Tomás, Claudio Giuliano: A semi-supervised approach to question classification.
• 
  Ruy Luiz Milidiú, Julio Cesar Duarte: Improving BAS committee performance with a semi-supervised approach.
• 
  Liva Ralaivola: Semi-supervised bipartite ranking with the normalized Rayleigh coefficient.
• 
  Etienne Côme, Latifa Oukhellou, Patrice Aknin, Thierry Denoeux: Partially-supervised learning in Independent Factor Analysis.

Dimensionality reduction

• 
  Axel Wismüller: The Exploration Machine - a novel method for structure-preserving dimensionality reduction.
• 
  Kerstin Bunte, Barbara Hammer, Petra Schneider, Michael Biehl: Nonlinear Discriminative Data Visualization.
• 
  Sebastian Bitzer, Stefan Klanke, Sethu Vijayakumar: Does dimensionality reduction improve the quality of motion interpolation?
• 
  Jaakko Luttinen, Alexander Ilin, Tapani Raiko: Transformations for variational factor analysis to speed up learning.
• 
  Paul Merlin, Antti Sorjamaa, Bertrand Maillet, Amaury Lendasse: X-SOM and L-SOM: a nested approach for missing value imputation.

Signal and image processing

• 
  Ladan Amini, Sophie Achard, Christian Jutten, Hamid Soltanian-Zadeh, Gholam-Ali Hossein-Zadeh, Olivier David, Laurent Vercueil: Sparse differential connectivity graph of scalp EEG for epileptic patients.
• 
  Arnaud de Decker, John Aldo Lee, Michel Verleysen: Patch-based bilateral filter and local m-smoother for image denoising.
• 
  John Aldo Lee, Arnaud de Decker, Michel Verleysen: Adaptive anisotropic denoising: a bootstrapped procedure.

Learning (with) preferences

• 
  Fabio Aiolli, Alessandro Sperduti: Supervised learning as preference optimization.
• 
  Eneldo Loza Mencía, Sang-Hyeun Park, Johannes Fürnkranz: Efficient voting prediction for pairwise multilabel classification.
• 
  Adriana Birlutiu, Perry Groot, Tom Heskes: Multi-task Preference learning with Gaussian Processes.

Learning I

• 
  Kerstin Bunte, Michael Biehl, Nicolai Petkov, Marcel F. Jonkman: Adaptive Metrics for Content Based Image Retrieval in Dermatology.
• 
  Xueru Zhang, Alexander Ypma, Bert de Vries: Bayesian periodogram smoothing for speech enhancement.
• 
  Benoît Frénay, Gael de Lannoy, Michel Verleysen: Improving the transition modelling in hidden Markov models for ECG segmentation.
• 
  Felipe Gerhard, Cristina Savin, Jochen Triesch: A robust biologically plausible implementation of ICA-like learning.
• 
  Vitaliy Kolodyazhniy: Spline-based neuro-fuzzy Kolmogorov's network for time series prediction.
• 
  Matthieu Sainlez, Pierre-Antoine Absil, Andrew E. Teschendorff: Gene expression data analysis using spatiotemporal blind source separation.
• 
  Christophe Boucher, Patrick Kouontchou, Bertrand Maillet, Raymond Hélène: A wavelet-heterogeneous index of market shocks for assessing the magnitude of financial crises.
• 
  Christophe Boucher, Bertrand Maillet, Paul Merlin: A robust hybrid DHMM-MLP modelling of financial crises measured by the WhIMS.
• 
  Yoan Miche, Amaury Lendasse: A faster model selection criterion for OP-ELM and OP-KNN: Hannan-Quinn criterion.
• 
  Jorge López Lázaro, José R. Dorronsoro: Rosen's projection method for SVM training.
• 
  Guillaume Chaslot, Jean-Baptiste Hoock, Fabien Teytaud, Olivier Teytaud: On the huge benefit of quasi-random mutations for multimodal optimization with application to grid-based tuning of neurocontrollers.
• 
  Caroline Bernard-Michel, Sylvain Douté, Mathieu Fauvel, Laurent Gardes, Stéphane Girard: Support vectors machines regression for estimation of mars surface physical properties.
• 
  Edouard Leclercq, Fabrice Druaux, Dimitri Lefebvre: Self-organising map for large scale processes monitoring.
• 
  René Meier, Lars Frank Große, Franz Joos: The Use of ANN for Turbo Engine Applications.

Efficient learning in recurrent networks

• 
  Barbara Hammer, Benjamin Schrauwen, Jochen J. Steil: Recent advances in efficient learning of recurrent networks.
• 
  Joschka Boedecker, Oliver Obst, Norbert Michael Mayer, Minoru Asada: Studies on reservoir initialization and dynamics shaping in echo state networks.
• 
  Xavier Dutoit, Benjamin Schrauwen, Hendrik Van Brussel: Non-markovian process modelling with Echo State Networks.
• 
  Claudius Gros, Gregor Kaczor: Stimulus processing and unsupervised learning in autonomously active recurrent networks.
• 
  Mark J. Embrechts, Luís A. Alexandre, Jonathan D. Linton: Reservoir computing for static pattern recognition.
• 
  Raymond H. Cuijpers, Floran Stuijt, Ida G. Sprinkhuizen-Kuyper: Generalisation of action sequences in RNNPB networks with mirror properties.
• 
  René Felix Reinhart, Jochen J. Steil: Attractor-based computation with reservoirs for online learning of inverse kinematics.

Classification and fuzzy logic

• 
  Catherine Krier, Damien François, Fabrice Rossi, Michel Verleysen: Supervised variable clustering for classification of NIR spectra.
• 
  Dietlind Zühlke, Tina Geweniger, Ulrich Heimann, Thomas Villmann: Fuzzy Fleiss-kappa for Comparison of Fuzzy Classifiers.
• 
  Rafal Dlugosz, Witold Pedrycz: Lukasiewicz fuzzy logic networks and their ultra low power hardware implementation.
• 
  Bernard Hugueney, Georges Hébrail, Yves Lechevallier, Fabrice Rossi: Simultaneous Clustering and Segmentation for Functional Data.

Neurosciences

• 
  Jean-Baptiste Passot, Laure Rondi-Reig, Angelo Arleo: Cerebellum and spatial cognition: A connectionist approach.
• 
  Agostino Gibaldi, Manuela Chessa, Andrea Canessa, Silvio P. Sabatini, Fabio Solari: A neural model for binocular vergence control without explicit calculation of disparity.

Weightless neural systems

• 
  Igor Aleksander, Massimo De Gregorio, Felipe Maia Galvão França, Priscila Machado Vieira Lima, Helen Morton: A brief introduction to Weightless Neural Systems.
• 
  Igor Aleksander, Helen Morton: Phenomenal weightless machines.
• 
  Bruno P. A. Grieco, Priscila Machado Vieira Lima, Massimo De Gregorio, Felipe Maia Galvão França: Extracting fuzzy rules from "mental" images generated by a modified WISARD perceptron.
• 
  Pierre Lorrentz, Gareth Howells, Klaus D. McDonald-Maier: FPGA-based enhanced probabilistic convergent weightless Network for human Iris recognition.
• 
  Konstantinos Sirlantzis, Gareth Howells, Bogdan Gherman: Novel Modular Weightless Neural Architectures for Biometrics-based Recognition.
• 
  Wilson Rosa de Oliveira: Quantum RAM Based Neural Netoworks.

Learning II

• 
  Mizuki Tsuta, Gamal El Masry, Takehiro Sugiyama, Kaori Fujita, Junichi Sugiyama: Comparison between linear discrimination analysis and support vector machine for detection of pesticide on spinach leaf by hyperspectral imaging with excitation-emission matrix.
• 
  Francisco J. Ruiz, Núria Agell, Cecilio Angulo: SVM-based learning method for improving colour adjustment in automotive basecoat manufacturing.
• 
  Tomasz Markiewicz, Stanislaw Osowski, Cezary Jochymski, Joanna Narbutt, Wojciech Kozlowski: Application of SVM for cell recognition in BCC skin pathology.
• 
  Hyunggi Cho, DaeEun Kim: A neural network model of landmark recognition in the fiddler crab, Uca lactea.
• 
  Charles Bouveyron, Camille Brunet, Vincent Vigneron: Classification of high-dimensional data for cervical cancer detection.
• 
  Kazuki Iwamura, Shigeo Abe: Sparse support vector machines by kernel discriminant analysis.
• 
  Cédric Simon, Christophe De Vleeschouwer, Jérôme Meessen: Embedding Proximal Support Vectors into Randomized Trees.
• 
  Friedhelm Schwenker, Amr Labib: Echo State networks and Neural network Ensembles to predict Sunspots activity.
• 
  Alexey Minin, Bernhard Lang: Monotonic Recurrent Bounded Derivative Neural Network.
• 
  Matthew D. Zeiler, Graham W. Taylor, Nikolaus F. Troje, Geoffrey E. Hinton: Modeling pigeon behavior using a Conditional Restricted Boltzmann Machine.
• 
  Lee Calcraft, Rod Adams, Neil Davey: Connection strategy and performance in sparsely connected 2D associative memory models with non-random images.
• 
  Thomas Burwick: Zero phase-lag synchronization through short-term modulations.
• 
  Michael Gutmann, Aapo Hyvärinen: Learning reconstruction and prediction of natural stimuli by a population of spiking neurons.

Brain Computer Interfaces: from theory to practice

• 
  Dieter Devlaminck, Bart Wyns, Luc Boullart, Patrick Santens, Georges Otte: Brain-Computer Interfaces: from theory to practice.
• 
  Wim van Drongelen, Hyong Lee, Amber Martell, Jennifer Dwyer, Rick Stevens, Mark Hereld: Oscillation in a network model of neocortex.
• 
  Bertrand Rivet, Antoine Souloumiac, Guillaume Gibert, Virginie Attina, Olivier Bertrand: Sensors selection for P300 speller brain computer interface.
• 
  Rolando Grave de Peralta Menendez, Jorge Dias, José Augusto Prado, Hadi Aliakbarpour, Sara González Andino: Multiclass brain computer interface based on visual attention.
• 
  Christoph Guger, Clemens Holzner, Christoph Groenegress, Günter Edlinger, Mel Slater: Brain Computer Interface for Virtual Reality Control.
• 
  Minoru Nakayama, Hiroshi Abe: The Possibility of Single-trial Classification of Viewed Characters using EEG Waveforms.
• 
  Ali Bahramisharif, Marcel van Gerven, Tom Heskes: Exploring the impact of alternative feature representations on BCI classification.
• 
  Cédric Gouy-Pailler, Jérémie Mattout, Marco Congedo, Christian Jutten: Uncued brain-computer interfaces: a variational hidden markov model of mental state dynamics.
• 
  Nanying Liang, Laurent Bougrain: Decoding finger flexion using amplitude modulation from band-specific ECoG.
• 
  Hubert Cecotti, Axel Graeser: Neural network pruning for feature selection - Application to a P300 Brain-Computer Interface.
• 
  Eric Demeester, Alexander Hüntemann, José del R. Millán, Hendrik Van Brussel: Augmenting Information from Brain-Computer Interfaces through Bayesian Plan Recognition.

Generative and bayesian models

• 
  Jörg Beyer, Kai Heesche, Werner Hauptmann, Clemens Otte: Heterogeneous mixture-of-experts for fusion of locally valid knowledge-based submodels.
• 
  Botond Bocsi, Lehel Csató: Dirichlet process-based component detection in state-space models.
• 
  Michail D. Vrettas, Dan Cornford, Yuan Shen: A variational radial basis function approximation for diffusion processes.
• 
  Faicel Chamroukhi, Allou Samé, Gérard Govaert, Patrice Aknin: A regression model with a hidden logistic process for signal parametrization.

Neural maps and learning vector quantization - theory and applications

• 
  Frank-Michael Schleif, Thomas Villmann: Neural Maps and Learning Vector Quantization - Theory and Applications.
• 
  Petra Schneider, Michael Biehl, Barbara Hammer: Hyperparameter Learning in Robust Soft LVQ.
• 
  Tina Geweniger, Dietlind Zühlke, Barbara Hammer, Thomas Villmann: Median Variant of Fuzzy c-Means.
• 
  Fabrice Rossi, Nathalie Villa: Topologically Ordered Graph Clustering via Deterministic Annealing.
• 
  Aree Witoelar, Michael Biehl, Barbara Hammer: Equilibrium properties of off-line LVQ.
• 
  Matthieu Geist, Olivier Pietquin, Gabriel Fricout: Kernelizing Vector Quantization Algorithms.
• 
  Axel Wismüller: A computational framework for exploratory data analysis.

Learning III

• 
  Miki Sirola, Jaakko Talonen, Golan Lampi: SOM based methods in early fault detection of nuclear industry.
• 
  Markus Hagenbuchner, Shujia Zhang, Ah Chung Tsoi, Alessandro Sperduti: Projection of undirected and non-positional graphs using Self Organizing Maps.
• 
  Marta Kolasa, Rafal Dlugosz: Hardware Implementation Issues of the Neighborhood Mechanism in Kohonen Self Organized Feature Maps.
• 
  Lucian Alecu, Hervé Frezza-Buet: Reconciling neural fields to self-organization.
• 
  Alberto Guillén, Luis Javier Herrera, Ginés Rubio, Héctor Pomares, Amaury Lendasse, Ignacio Rojas: Applying Mutual Information for Prototype or Instance Selection in Regression Problems.
• 
  Erik Schaffernicht, Christoph Möller, Klaus Debes, Horst-Michael Gross: Forward feature selection using Residual Mutual Information.
• 
  Nisrine Jrad, Edith Grall-Maës, Pierre Beauseroy: Gaussian Mixture Models for multiclass problems with performance constraints.
• 
  Johannes Partzsch, René Schüffny: On the routing complexity of neural network models - Rent's Rule revisited.

last updated on Sat May 25 04:57:12 2013 by the dblp team
data released under the ODC-BY 1.0 license
see also our legal information page