Function Basis Function (2009)
dimensional data are data are difficult difficult to to represent represent difficult difficult to to understand understand difficult difficult to to analyze analyze
Emission Modelling for Supervised ECG Segmentation using Finite Differences (2009)
B. Frénay, G. De Lannoy, M. Verleysen
Abstract — The segmentation of ECG signals into P waves, QRS complexes, T waves and baselines is an important practical problem for physicians diagnosing cardiac diseases. The duration of the...
Supervised ECG Delineation Using the Wavelet Transform and Hidden Markov Models (2009)
G. De Lannoy, B. Frenay, M. Verleysen, J. Delbeke
Abstract — Clinical monitoring and pharmaceutical phaseone studies require feature extraction from the ECG signal in order to evaluate the state of a patient’s heart. Automatic annotation of the...
A Supervised Wavelet Transform Algorithm for R Spike Detection in Noisy ECGs ⋆ (2009)
G. De Lannoy, A. De Decker, M. Verleysen
Abstract. The wavelet transform is a widely used pre-filtering step for subsequent R spike detection by thresholding of the coefficients. The time-frequency decomposition is indeed a powerful tool to...
G. De Lannoy, A. De Decker, M. Verleysen
Continuous wavelet transform, automatic ECG annotation, R spike detection, supervised learning. One of the most important tasks in automatic annotation of the ECG is the detection of the R spike. The...
Filtering Heart Related Activity from Vagus Nerve Recordings in Rats (2009)
G. De Lannoy, J. Marin, M. Verleysen, J. Delbeke
Vagus nerve stimulation has become a recognized form of treatment for several conditions such as refractory epilepsy and depression. However, its exact mechanism of interference with these...
S. Dablemont, S. Van Bellegem, M. Verleysen
The analysis of financial time series is very useful in the economic world. This paper deals with a data-driven empirical analysis of financial time series. In this paper we present a forecasting...
G. De Lannoy, A. De Decker, M. Verleysen
Abstract: One of the most important tasks in automatic annotation of the ECG is the detection of the R spike. The wavelet transform is a widely used tool for R spike detection. The time-frequency...
Feature clustering and mutual information for the selection of variables in spectral data (2009)
C. Krier, D. François, F. Rossi, M. Verleysen
Abstract. Spectral data often have a large number of highly-correlated features, making feature selection both necessary and uneasy. A methodology combining hierarchical constrained clustering of...
Functional SOM for variable-length signal windows (2009)
A. De Decker, G. De Lannoy, M. Verleysen
Abstract — Functional data are often sampled at high frequency which leads to high-dimensional vectors. The curse of dimensionality makes this type of signal difficult to handle with standard data...
Time Series Forecasting using CCA and Kohonen Maps- Application to Electricity Consumption (2008)
A. Lendasse, J. Lee, V. Wertz, M. Verleysen, Av. G. Lemaître
Abstract. A general-purpose useful parameter in time series forecasting is the regressor, corresponding to the minimum number of variables necessary to forecast the future values of the time series....
Some examples Some examples The Gaussian case The Gaussian case (2008)
M. Verleysen, M. Verleysen, Uncorrelation Vs Independence, M. Verleysen
Blind source separation & cocktail party problem Blind source separation & cocktail party problem Equations, indeterminations & assumptions Equations, indeterminations & assumptions...
Effective Input Variable Selection for Function Approximation (2008)
L. J. Herrera, H. Pomares, I. Rojas, M. Verleysen, A. Guilén
Abstract. Input variable selection is a key preprocess step in any I/O modelling problem. Normally, better generalization performance is obtained when unneeded parameters coming from irrelevant or...
Determination of the Mahalanobis Matrix using Nonparametric Noise Estimations (2008)
A. Lendasse, F. Corona, J. Hao, N. Reyhani, M. Verleysen
Abstract. In this paper, the problem of an optimal transformation of the input space for function approximation problems is addressed. The transformation is defined determining the Mahalanobis matrix...
Abstract On the Extraction of the Snore Acoustic Signal by Independent Component Analysis (2008)
F. Vrins, J. Deswert, D. Bouvy, V. Bouillon, J. A. Lee, C. Eugène, ...
Physicians are interested in the acoustic signal of snore, because it allows them to diagnose the patient and eventually to avoid several dangerous accidents. Today, its measure is not satisfactory...
Feature Scoring by Mutual Information for Classification of (2008)
C. Krier, D. François, V. Wertz, M. Verleysen
Selecting relevant features in mass spectra analysis is important both for classification and search for causality. In this paper, it is shown how using mutual information can help answering to both...
R. Sameni, F. Vrins, F. Parmentier, C. Hérail, V. Vigneron, M. Verleysen, ...
Abstract. Blind source separation (BSS) techniques have revealed to be promising approaches for the noninvasive extraction of fetal cardiac signals from maternal abdominal recordings. From previous...
Local Vector-based Models for Sense Discrimination (2008)
De Marnee Archambeau, C. Archambeau, P. Dupont, M. Verleysen
Word sense discrimination aims at automatically determining which instances of an ambiguous word share the same sense. A fully unsupervised technique based on a high dimensional vector representation...
Model-Based Reinforcement Learning with Continuous States and Actions (2008)
Deisenroth, M.P., Rasmussen, C.E., Peters, J., Verleysen, M.
Finding an optimal policy in a reinforcement learning (RL) framework with continuous state and action spaces is challenging. Approximate solutions are often inevitable. GPDP is an approximate dynamic...
Learning Inverse Dynamics: A Comparison (2008)
Nguyen-Tuong, D., Peters, J., Seeger, M., Schölkopf, B., Verleysen, M.
While it is well-known that model can enhance the control performance in terms of precision or energy efficiency, the practical application has often been limited by the complexities of manually...
A CMOS/SOI Continuous-Time Low-Pass gm-C Filter (2007)
This paper describes a preliminary comparative analysis between continuous-time gm-C filters based on a specific transcondutor but designed according to CMOS/bulk (conventional) and CMOS/SOI...
SELECTIVE STIMULATION OF THE HUMAN OPTIC NERVE (2007)
C. Veraart, J. Delbeke, A. Vanlierde, G. Michaux, S. Parrini, ...
A blind volunteer affected with retinitis pigmentosa was intracranially implanted with a selfsizing cuff electrode around her right optic nerve. The nerve cuff electrode included 4 monopolar...
Classification of investment funds by self-organizing maps (2007)
P. Cardon, A. Lendasse, V. Wertz, E. De Bodt, M. Verleysen, ...
An investment fund (or mutual fund) is an investment structure collecting money coming from individuals and investing according to preestablished objectives. Professional managers decide of the...
Application to the Bel 20 (2007)
A. Lendasse, E. De Bodt, V. Wertz, M. Verleysen
Non-linear financial time series forecasting –
A. Lendasse, M. Cottrell, V. Wertz, M. Verleysen
Abstract. The problem of electrical load forecasting presents some particularities, compared to the generic problem of time-series prediction. One of these particularities is that several values...
M. Verleysen, E. De Bodt, A. Lendasse
Abstract. A crucial problem in non-linear time series forecasting is to determine its auto-regressive order, in particular when the prediction method is non-linear. We show in this paper that this...
E Catholique, De Louvain, Co-promoteurs Dr, M. Verleysen, Dr. Y. Kamp
M'emoire pr'esent'e en vue de l'obtention du grade d'ing'enieur civil en informatique par Antoine Choppin Louvain-la-Neuve Ann'ee acad'emique 1997--1998...
Should Seed Investors Read Business Plans? (2007)
D. Francois, B. Gailly, A. Lendasse, V. Wertz, M. Verleysen
A business plan is a document presenting in a concise form the key elements (management, finance, marketing, ...) describing a percieved business opportunity. It is used among others as a tool for...
N. Delannay, F. Rossi, B. Conan-guez, M. Verleysen
Abstract. There has been recently a lot of interest for functional data analysis [1] and extensions of well-known methods to functional inputs (clustering algorithm [2], non-parametric models [3],...
M. Verleysen, M. Verleysen, M. Verleysen, Pca Pca, M. Verleysen, M. Verleysen
finding a transformation that decorrelates the variables � � ICA: ICA: finding a transformation that make variables as independent as possible � � In this lecture: the transformation is...
� � Example y Data Model (2007)
M. Verleysen, What Is Clustering, M. Verleysen, M. Verleysen, M. Verleysen, ...
� � kk-NN NN classification and regression
M. Verleysen, G. Simon, M. Verleysen, G. Simon, M. Verleysen, G. Simon, ...
� � Kohonen’s Kohonen s self-organizing self organizing maps – SOM intuition and equations – SOM parameters: grid shape, learning rate, neighbourhood – Distance measures � � SOM...
Mixing and non-mixing local minima of the entropy contrast for blind source separation (2006)
In this paper, both non-mixing and mixing local minima of the entropy are analyzed from the viewpoint of blind source separation (BSS); they correspond respectively to acceptable and spurious...
The permutation test for feature selection by mutual information (2006)
D. François, V. Wertz, M. Verleysen
Abstract. The estimation of mutual information for feature selection is often subject to inaccuracies due to noise, small sample size, bad choice of parameter for the estimator, etc. The choice of a...
Fast Bootstrap Methodology For Regression Model Selection (2005)
A. Lendasse, G. Simon, V. Wertz, M. Verleysen
Usii resampliA methodslih cross-valiqAkBR and bootstrapi a necessik i neural network desikA forsolvi; the problem of model structureselectiA; The bootstrapi a powerful method offerix a lowvariBTx of...
Vector Quantization: A Weighted Version For Time-Series Forecasting (2005)
A. Lendasse, D. Francois, V. Wertz, M. Verleysen
Nonlinear time-series prediction offers potential performance increases compared to linear models. Nevertheless, the enhanced complexity and computation time often prohibits an efficient use of...
Non-Euclidean metrics for similarity search in noisy datasets (2005)
D. Francois, V. Wertz, M. Verleysen
In the context of classification, the dissimilarity between data elements is often measured by a metric defined on the data space. Often, the choice of the metric is often disregarded and the...
Supervised nonparametric information theoretic classification (2004)
Archambeau, C., Butz, T., Popovici, V., Verleysen, M., Thiran, J.
Functional radial basis function network (2004)
N. Delannay, F. Rossi, B. Conan-guez, M. Verleysen
Abstract. There has been recently a lot of interest for functional data analysis [1] and extensions of well-known methods to functional inputs (clustering algorithm [2], non-parametric models [3],...
Functional Radial Basis Function Networks (2004)
Frbfn Delannay Rossi, N. Delannay, F. Rossi, B. Conan-guez, M. Verleysen
There has been recently a lot of interest for functional data analysis [1] and extensions of well-known methods to functional inputs (clustering algorithm [2], non-parametric models [3], MLP [4]).
F. Vrins, V. Vigneron, C. Jutten, M. Verleysen
Obstetricians were asking the engineering support to study more extensively any technical possibility to electronically get some useful information from the whole PQRST complex of the fetal...
Fast bootstrap for least-square support vector machines (2004)
A. Lendasse, G. Simon, V. Wertz, M. Verleysen
Abstract. The Bootstrap resampling method may be efficiently used to estimate the generalization error of nonlinear regression models, as artificial neural networks and especially Least-square...
On the Effects of Dimensionality on Data Analysis With Neural Networks (2003)
M. Verleysen, D. Francois, G. Simon, V. Wertz
Modern data analysis often faces high-dimensional data.
Fast Approximation of the Bootstrap for Model Selection (2003)
G. Simon, A. Lendasse, V. Wertz, M. Verleysen
The bootstrap resampling method may be efficiently used to estimate the generalization error of a family of nonlinear regression models, as artificial neural networks. The main difficulty associated...
Approximation by Radial Basis Function Networks - Application to Option Pricing (2003)
A. Lendasse, J. Lee, E. De Bodt, V. Wertz, M. Verleysen
We propose a method of function approximation by radial basis function networks. We will demonstrate that this approximation method can be improved by a pre-treatment of data based on a linear model....
Nonlinear Time Series Prediction by Weighted Vector Quantization (2003)
A. Lendasse, D. Francois, V. Wertz, M. Verleysen
Classical nonlinear models for time series prediction exhibit improved capabilities compared to linear ones. Nonlinear regression has however drawbacks, such as overfitting and local minima problems,...
Improving independent component analysis performances by variable selection (2003)
F. Vrins, J. A. Lee, M. Verleysen, V. Vigneron, C. Jutten
Abstract. Blind Source Separation (BSS) consists in recovering unobserved signals from observed mixtures of them. In most cases the whole set of mixtures is used for the separation, possibly after a...
Input data reduction for the prediction of financial time series (2001)
A. Lendasse, J. Lee, E. Debodt, V. Wertz, M. Verleysen, ...
Abstract. Prediction of financial time series using artificial neural networks has been the subject of many publications, even if the predictability of financial series remains a subject of...
A statistical tool to assess the reliability of self-organizing maps (2001)
M. Cottrell, E. De Bodt, M. Verleysen
3 Université catholique de Louvain, DICE, 3, place du Levant,