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20062009
most citedMutual information for the selection of relevant variables in spectrometric nonlinear modelling

219 citations · 1k across the 15 of their papers we have counts for

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6 papers · 1 filter

cs.NE200834 cited

A data-driven functional projection approach for the selection of feature ranges in spectra with ICA or cluster analysis

Catherine Krier, Fabrice Rossi, Damien François +1

Prediction problems from spectra are largely encountered in chemometry. In addition to accurate predictions, it is often needed to extract information about which wavelengths in th…

cs.NE2008

Multi-Layer Perceptrons and Symbolic Data

Fabrice Rossi, Brieuc Conan-Guez

In some real world situations, linear models are not sufficient to represent accurately complex relations between input variables and output variables of a studied system. Multilay…

cs.NE2007135 cited

Functional Multi-Layer Perceptron: a Nonlinear Tool for Functional Data Analysis

Fabrice Rossi, Brieuc Conan-Guez

In this paper, we study a natural extension of Multi-Layer Perceptrons (MLP) to functional inputs. We show that fundamental results for classical MLP can be extended to functional…

cs.NE2007126 cited

Representation of Functional Data in Neural Networks

Fabrice Rossi, Nicolas Delannay, Brieuc Conan-Guez +1

Functional Data Analysis (FDA) is an extension of traditional data analysis to functional data, for example spectra, temporal series, spatio-temporal images, gesture recognition da…

cs.NE20075 cited

Self-organizing maps and symbolic data

Aïcha El Golli, Brieuc Conan-Guez, Fabrice Rossi

In data analysis new forms of complex data have to be considered like for example (symbolic data, functional data, web data, trees, SQL query and multimedia data, ...). In this con…

cs.NE200749 cited

Fast Algorithm and Implementation of Dissimilarity Self-Organizing Maps

Brieuc Conan-Guez, Fabrice Rossi, Aïcha El Golli

In many real world applications, data cannot be accurately represented by vectors. In those situations, one possible solution is to rely on dissimilarity measures that enable sensi…