Electronic proceedings author index

A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | Z
M. Verleysen
  • ESANN 1993 - Laplacian pyramid with multilayer perceptrons interpolators [Details]
  • ESANN 1993 - Optimal decision surfaces in LVQ1 classiffication of patterns [Details]
  • ESANN 1994 - An optimized RBF network for approximation of functions [Details]
  • ESANN 1994 - Estimation of performance bounds in supervised classification [Details]
  • ESANN 1995 - Suboptimal Bayesian classification by vector quantization with small clusters [Details]
  • ESANN 1997 - Kohonen maps versus vector quantization for data analysis [Details]
  • ESANN 1998 - Forecasting time-series by Kohonen classification [Details]
  • ESANN 1999 - Extraction of intrinsic dimension using CCA - Application to blind sources separation [Details]
  • ESANN 1999 - Using the Kohonen algorithm for quick initialization of Simple Competitive Learning algorithm [Details]
  • ESANN 2000 - A robust non-linear projection method [Details]
  • ESANN 2000 - Time series forecasting using CCA and Kohonen maps - application to electricity consumption [Details]
  • ESANN 2001 - Input data reduction for the prediction of financial time series [Details]
  • ESANN 2002 - Curvilinear Distance Analysis versus Isomap [Details]
  • ESANN 2002 - Width optimization of the Gaussian kernels in Radial Basis Function Networks [Details]
  • ESANN 2003 - Fast approximation of the bootstrap for model selection [Details]
  • ESANN 2003 - Locally Linear Embedding versus Isotop [Details]
  • ESANN 2003 - On Convergence Problems of the EM Algorithm for Finite Gaussian Mixtures [Details]
Michel Verleysen
  • ESANN 2004 - Towards a Local Separation Performances Estimator Using Common ICA Contrast Functions ? [Details]
  • ESANN 2005 - Non-Euclidean metrics for similarity search in noisy datasets [Details]
  • ESANN 2005 - Pruned lazy learning models for time series prediction [Details]
  • ESANN 2005 - clustering using a random walk based distance measure [Details]
  • ESANN 2006 - Determination of the Mahalanobis matrix using nonparametric noise estimations [Details]
  • ESANN 2006 - Lag selection for regression models using high-dimensional mutual information [Details]
  • ESANN 2006 - Non-orthogonal Support Width ICA [Details]
  • ESANN 2006 - The permutation test for feature selection by mutual information [Details]
  • ESANN 2007 - Collaborative Filtering with interlaced Generalized Linear Models [Details]
  • ESANN 2007 - Feature clustering and mutual information for the selection of variables in spectral data [Details]
  • ESANN 2007 - Mixtures of robust probabilistic principal component analyzers [Details]
  • ESANN 2008 - K-nearest neighbours based on mutual information for incomplete data classification [Details]
  • ESANN 2008 - Nonlinear data projection on a sphere with controlled trade-off between trustworthiness and continuity [Details]
  • ESANN 2008 - Rank-based quality assessment of nonlinear dimensionality reduction [Details]
  • ESANN 2008 - Using the Delta Test for Variable Selection [Details]
  • ESANN 2009 - Adaptive anisotropic denoising: a bootstrapped procedure [Details]
  • ESANN 2009 - Improving the transition modelling in hidden Markov models for ECG segmentation [Details]
  • ESANN 2009 - Patch-based bilateral filter and local m-smoother for image denoising [Details]
  • ESANN 2009 - Supervised variable clustering for classification of NIR spectra [Details]
  • ESANN 2010 - Ensemble Modeling with a Constrained Linear System of Leave-One-Out Outputs [Details]
  • ESANN 2010 - Mode estimation in high-dimensional spaces with flat-top kernels: application to image denoising [Details]
  • ESANN 2010 - Recent Advances in Nonlinear Dimensionality Reduction, Manifold and Topological Learning [Details]
  • ESANN 2010 - Self Organizing Star (SOS) for health monitoring [Details]
  • ESANN 2010 - Using SVMs with randomised feature spaces: an extreme learning approach [Details]
  • ESANN 2011 - Class-Specific Feature Selection for One-Against-All Multiclass SVMs [Details]
  • ESANN 2011 - Mutual information based feature selection for mixed data [Details]
  • ESANN 2011 - Mutual information for feature selection with missing data [Details]
  • ESANN 2012 - Cluster homogeneity as a semi-supervised principle for feature selection using mutual information [Details]
  • ESANN 2012 - Incremental feature building and classification for image segmentation [Details]
  • ESANN 2012 - On the Potential Inadequacy of Mutual Information for Feature Selection [Details]
  • ESANN 2012 - The stability of feature selection and class prediction from ensemble tree classifiers [Details]
  • ESANN 2013 - Risk Estimation and Feature Selection [Details]
  • ESANN 2013 - Sensitivity to parameter and data variations in dimensionality reduction techniques [Details]
  • ESANN 2014 - Interactive dimensionality reduction for visual analytics [Details]
  • ESANN 2014 - Multiscale stochastic neighbor embedding: Towards parameter-free dimensionality reduction [Details]
  • ESANN 2014 - Recent methods for dimensionality reduction: A brief comparative analysis [Details]
  • ESANN 2015 - Geometrical homotopy for data visualization [Details]
  • ESANN 2016 - A state-space model on interactive dimensionality reduction [Details]
  • ESANN 2018 - Extensive assessment of Barnes-Hut t-SNE [Details]
  • ESANN 2018 - Perplexity-free t-SNE and twice Student tt-SNE [Details]
  • ESANN 2019 - Class-aware t-SNE: cat-SNE [Details]
  • ESANN 2019 - MAP best performances prediction for endurance runners [Details]
  • ESANN 2019 - Tensor factorization to extract patterns in multimodal EEG data [Details]
Abhishek Verma
  • No papers found
B.K. Verma
  • ESANN 1995 - A new training algorithm for feedforward neural networks [Details]
Richa Verma
  • ESANN 2018 - Evolutionary RL for Container Loading [Details]
A. Vermeulen
  • ESANN 1995 - Some new results on the coding of pheromone intensity in an olfactory sensory neuron [Details]
Pierre Vernimmen
  • ESANN 2024 - Convergence analysis of an inexact gradient method on smooth convex functions [Details]
H. Verrelst
  • ESANN 1999 - A hybrid system for fraud detection in mobile communications [Details]
Tom Verresen
  • ESANN 2025 - Exploring Model Architectures for Real-Time Lung Sound Event Detection [Details]
Alessandro Verri
  • ESANN 2005 - Support vector algorithms as regularization networks [Details]
  • ESANN 2008 - A method for robust variable selection with significance assessment [Details]
  • ESANN 2010 - A randomized algorithm for spectral clustering [Details]
  • ESANN 2012 - Adaptive Optimization for Cross Validation [Details]
  • ESANN 2012 - Discriminant functional gene groups identification with machine learning and prior knowledge [Details]
  • ESANN 2013 - A dictionary learning based method for aCGH segmentation [Details]
A. Verri
  • ESANN 1999 - Support vector machines vs multi-layer perceptrons in particle identification [Details]
Mario Versaci
  • ESANN 2004 - Disruption Anticipation in Tokamak Reactors: A Two-Factors Fuzzy Time Series Approach [Details]
Robin Verschuren
  • ESANN 2024 - Graph-cut-assisted CNN training for pulmonary embolism segmentation [Details]
C. Versino
  • ESANN 1993 - An intuitive characterization for the reference vectors of a Kohonen map [Details]
Timothy Verstraeten
  • ESANN 2019 - Deep hybrid approach for 3D plane segmentation [Details]
David Verstraeten
  • ESANN 2005 - Isolated word recognition using a Liquid State Machine [Details]
  • ESANN 2007 - Adapting reservoir states to get Gaussian distributions [Details]
  • ESANN 2007 - An overview of reservoir computing: theory, applications and implementations [Details]
  • ESANN 2010 - Extending reservoir computing with random static projections: a hybrid between extreme learning and RC [Details]
Lyan Verwimp
  • ESANN 2020 - On the long-term learning ability of LSTM LMs [Details]
Jean-Marc Vesin
  • ESANN 2006 - Spatial filters for the classification of event-related potentials [Details]
Benedikt Vettelschoss
  • ESANN 2020 - Self-organized dynamic attractors in recurrent neural networks [Details]
Sebastian Vetter
  • ESANN 2021 - AGLVQ - Making Generalized Vector Quantization Algorithms Aware of Context [Details]
Giuseppe Vettigli
  • ESANN 2021 - Weightless Neural Networks for text classification using tf-idf [Details]
Gizelle Vianna
  • ESANN 2017 - A decision support system based on cellular automata to help the control of late blight in tomato cultures [Details]
Dolores Vicente
  • ESANN 2005 - Handling outliers and missing data in brain tumour clinical assessment using t-GTM [Details]
A. Vicino
  • ESANN 2000 - Financial predictions based on bootstrap-neural networks [Details]
F.J. Vico
  • ESANN 1993 - Modelling biological learning from its generalization capacity [Details]
Quentin Victor
  • ESANN 2025 - Investigating four deep learning approaches as candidates for unified models in time series forecasting and event prediction: application in anesthesia training [Details]
Eva Vidal
  • ESANN 2004 - BIOSEG: a bioinspired vlsi analog system for image segmentation [Details]
Franck Vidal
  • ESANN 2005 - Neuromimetic model of interval timing [Details]
David Vieira
  • ESANN 2016 - Sparse Least Squares Support Vector Machines via Multiresponse Sparse Regression [Details]
Daniel Vieira
  • ESANN 2018 - Vector Field Based Neural Networks [Details]