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Summary
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1999 –
today
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International
patents: 3 (+2)
International
journals: 9 (+1)
International
conferences: 18
International
workshops: 5
International
invited talks: 1
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National journals: 5
National
conferences: 14
National
workshops: 4
National invited
talks: 3
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Patents
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2014
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M. Aupetit, J.
Gil-Quijano
Distributed
system based on topology learning for indoor localization and mapping. To be submitted
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To
be submitted
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2012
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R. de Aldama,
M. Aupetit, J.-P. Poli,
L. Boudet,
Optimization
method and system of a Fuzzy-Rule Based System
preserving knowledge interpretability. Patent Pending
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Pending
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2010
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S. Lespinats,
M. Aupetit,
Method
and system for evaluating the class of test data in a large-dimension data
space.
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WO/2011/047889
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M.
Aupetit, S. Lespinats,
Method and system
for evaluating the resemblance of a query object to reference objects.
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WO/2011/048219
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2009
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P. Gaillard, M. Aupetit,
Semi-supervised
learning method system for data classification according to discriminating
parameters.
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EP2180436A1
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Journals (national/international)
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2014
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Sylvain Lespinats, Michaël Aupetit
ClassiMap: a supervised multidimensional scaling
technique which preserves the topology of the classes
Submitted to Neurocomputing
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(Neurocomputing)
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2011
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Sylvain Lespinats, Michaël
Aupetit.
CheckViz : sanity check and
topological clues for linear and nonlinear mappings (fast track EuroVis2010)
Computer Graphics
Forum journal, 30(1) july 2011, pp. 113–125, Eurographics
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CGF
2011
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2010
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M. Aupetit
WinSitu, un nouveau paradigme
pour l’analyse exploratoire
de données basée sur des projections
Revue des Nouvelles Technologies de l’Information
(RNTI A3) Cépaduès Editions, 2010
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RNTI
2010
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P. Gaillard, M. Aupetit, G. Govaert
Un graphe génératif pour la
classification
semi-supervisée
Ingénierie
des Systèmes d'Information
Vol. 15, Avril 2010
http://isi.revuesonline.com/
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ISI
2010
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2009
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Michaël Aupetit.
Nearly homogeneous multi-partitioning with a
deterministic generator
Neurocomputing, 72(7-9), March 2009,
1379-1389, Elsevier
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Neurocomputing 2009
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M. Aupetit, P. Gaillard, G. Govaert
Un modèle génératif pour l’apprentissage de la topologie
Apprentissage et fouille de données -Revue des
Nouvelles Technologies de l’Information
(RNTI A3) Cépaduès Editions, pages 49 à 76, juillet 2009
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RNTI
2009
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2008
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Rémi Bossu, Gilles Mazet-Roux,
Vincent Douet, Sergio Rives, Sylvie Marin, Michaël Aupetit,
Internet Users as Seismic Sensors for Improved
Earthquake Response
EOS pp. 230-231, 2008
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EOS
2008
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Gaillard Pierre, Michaël Aupetit, Gérard Govaert.
Learning topology of a labeled
data set with the supervised
generative Gaussian graph
Neurocomputing, 71(7-9) March 2008,
1283-1299, Elsevier
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Neurocomputing 2008
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M. Aupetit, P. Gaillard
Mesurer et visualiser
les distorsions dans
les techniques de projection continues
Revue Sciences et
Techniques de l’Ingénieur – Revue d’Intelligence Artificielle –
22/2008. Visualisation et extraction des connaissances, pages 443 à 472
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RIA
2008
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2007
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Dominique Lepetz, Max Nemoz-Gaillard,
Michaël Aupetit
Concerning the differentiability of the energy function in vector
quantization algorithms
Neural Networks, Volume
20, July 2007, Pages 621-630. Elsevier
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Neural Networks
2007
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Michaël Aupetit,
Visualizing distortions and recovering topology in continuous
projection techniques.
Neurocomputing 70(7-9):1304-1330,
March 2007 Advances in Computational Intelligence and Learning - 14th
European Symposium on Artificial Neural Networks 2006,
http://dx.doi.org/10.1016/j.neucom.2006.11.018
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Neurocomputing 2007
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2006
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David Mercier, Pierre
Gaillard, Michaël Aupetit,
Carole Maillard, Robert Quach
and Jean-Denis Muller,
How to help seismic analysts to verify the French seismic bulletin?
Engineering
Applications of Artificial Intelligence, Volume 19, Issue 7, October 2006, Pages
797-806, Elsevier.
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EAAI
2006
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2005
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Michaël Aupetit, Thibaud Catz,
High-dimensional labeled data analysis
with topology representing graphs.
Neurocomputing 63, 139-169, Elsevier 2005.
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Neurocomputing 2005
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J.-D . Muller, M. Aupetit,
D. Mercier
Analyse d’événements sismiques par
Intelligence Artificielle
CHOCS – Revue scientifique
et technique de la direction des applications militaires.
N°31. Octobre 2005
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CHOCS
2005
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2002
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Michaël Aupetit, Pierre
Couturier, Pierre Massotte
g-Observable neighbours for vector quantization
Neural Networks, Volume
15, Issues 8-9, October-November 2002, Pages 1017-1027. Elsevier
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Neural Networks
2002
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Conferences (national/international)
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2014
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Michaël Aupetit
Sanity
Check for Class-coloring-based Evaluation of Dimension Reduction techniques
BELIV workshop at
IEEE VIS 2014 Beyond Time and Errors: Novel Evaluation Methods for
Visualization, Paris, France, November 2014
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BELIV2014
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Michaël Aupetit, Nicolas Heulot,
Jean-Daniel Fekete
A
multidimensional brush for scatterplot data analytics
Poster at IEEE VIS 2014 conference,
Paris, France, November 2014
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IEEE VIS2014
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Ricardo de Aldama, Michaël Aupetit
Interpretability
in Fuzzy Systems Optimization: A Topological Approach
15th International
Conference on Information Processing and Management of Uncertainty in
Knowledge-Based Systems, Montpellier, France, July 2014.
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IPMU 2014
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2013
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Ricardo de Aldama, Michaël Aupetit
Preserving
Interpretability in the Optimization of Fuzzy Systems: a Generic Algorithm
in a Topological Framework
22e Rencontres Francophones sur la Logique Floue et ses Applications,
Reims, France, October 2013
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LFA
2013
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Sylvain Lespinats, Michaël Aupetit,
ClassiMap : a Supervised Mapping Technique for
Decision Support
EuroVis 2013 Workshop on
Visual analytics using Multidimensional Projections, Leipzig, Germany, June
2013
http://homepage.tudelft.nl/19j49/eurovis2013/
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VAMP@
EuroVis
2013
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Nicolas Heulot, Michaël Aupetit, Jean-Daniel Fekete,
ProxiLens: Interactive Exploration of
High-Dimensional Data using Projections
EuroVis 2013 Workshop on
Visual analytics using Multidimensional Projections, Leipzig, Germany, June
2013
http://homepage.tudelft.nl/19j49/eurovis2013/
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VAMP@
EuroVis
2013
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Maxime Maillot, Michaël Aupetit, Gérard Govaert
Extraction
des nombres de Betti
avec un modèle génératif
EGC2013,
Toulouse, France, January 2013
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EGC
2013
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2012
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Maxime Maillot, Michael
Aupetit and Gerard Govaert,
The
Generative Simplicial Complex to extract Betti numbers from unlabeled data.
NIPS 2012
Workshop on Algebraic Topology and Machine Learning. Lake Tahoe, USA,
December 2012
https://sites.google.com/site/nips2012topology/
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ATML@
NIPS
2012
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Nicolas Heulot, Michaël Aupetit, Jean-Daniel Fekete,
ProxiViz: an Interactive Visualization Technique
to
Overcome Multidimensional Scaling Artifacts
Poster, IEEE InfoVis 2012, Seattle, October 2012
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InfoVis
2012
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Maxime Maillot, Michaël Aupetit, Gérard Govaert,
A
generative model that learns Betti numbers from a
data set
ESANN’12
conference, Bruges, Belgium, April 2012
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ESANN
2012
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Nicolas Heulot, Michaël Aupetit, Jean-Daniel Fekete,
Évaluation de ProxiViz
pour la fouille visuelle
de données Multidimensionnelles
EGC2012 Workshop Fouille Visuelle de Données, Bordeaux, France, January 2012
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FVD@
EGC
2012
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2011
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Michaël Aupetit, Nicolas Heulot,
WinSitu : un nouveau paradigme
pour la visualisation de données
multidimensionnelles
VISU 2011, Bruyères-le-Châtel, France,
October 2011
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VISU
2011
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2010
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M. Aupetit, L. Allano, I. Espagnon, G. Sannie
Visual Analytics to Check Marine Containers in the
Eritr@c Project
Proc. of the International Symposium on Visual Analytics Science and
Technology (EuroVAST),
J. Kohlhammer and D. Keim
(Editors), pp. 57-60, Bordeaux, June 2010
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EuroVAST
2010
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S. Lespinats, M. Aupetit
Mapping without visualizing local default is
nonsense
Proc. of European
Symposium on Artificial Neural Networks,
Bruges, pp. 111-116, April 2010
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ESANN 2010
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Lorène Allano, Michaël Aupetit, Guillaume Sannié,
Le projet Eritr@c : du neutron à
l'aide à la décision
pour
le contrôle de conteneurs
WISG 2012, Troye, France, January 2010
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WISG
2010
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2009
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S. Lespinats, M. Aupetit
False neighbourhoods and tears are the main
mapping
defaults. How to avoid
it? How to exhibit remaining
ones?
Proc. of Workshop on Quality Issues, Measures of Interestingness and
Evaluation of data mining models (QIMIE) hosted by PAKDD2009, pp 55-65, Bangkok, Thailand, April 27-30, 2009
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QIMIE@
PAKDD
2009
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M. Aupetit
La
divergence de Hausdorff et un algorithme
glouton de partitionnement
homogène
Actes du congrès CAp2009, Hammamet,
May 2009
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Cap
2009
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2008
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M. Aupetit
Homogeneous bipartition based on multidimensional
ranking
Proc. of European Symposium on Artificial Neural
Networks, Bruges, April 2008
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ESANN 2008
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2007
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P. Gaillard, M. Aupetit
Learning Topology of labeled
data set with the Supervised GGG
Proc. of Europ. Symp. on Artificial
Neural Networks, Bruges, April 2007
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ESANN 2007
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P. Gaillard, M. Aupetit
Apprentissage statistique de
la topologie d'un ensemble de données
étiquetées Actes du
congrès CAp2007, July 2007, Grenoble
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Cap
2007
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P. Gaillard, M. Aupetit
Apprentissage statistique de
la topologie d'un ensemble de données
étiquetées Actes des Journées Francophones d’Extraction et de Gestion
des Connaissances (EGC 2007) January 2007
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EGC
2007
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2006
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Michaël Aupetit
Learning Topology with the Generative Gaussian
Graph and the EM algorithm
Advances in Neural Information Processing and
Systems 18, Proceedings of the 2005 Conference,
Yair Weiss, Bernhard Schölkopf
and John C. Platt, eds., pp.83-90, 2006.
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NIPS
2005
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Michaël Aupetit
Visualizing the trustworthiness of a projection.
Proc. of European Symposium on Artificial Neural
Networks (ESANN’2006), Bruges, April 2006. Editor Michel Verleysen, d-side, pp. 271-276.
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ESANN 2006
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Laurence Cornez, Michaël
Aupetit, Manuel Samuelidès
Les ensembles flous dans les arbres de décision et les
mélanges d’experts : vers une
solution de discrimination intelligible des données
sismiques ?
Actes des Rencontres francophones sur la Logique Floue et ses Applications (LFA 2006) Toulouse, 19-20 October
2006
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LFA
2006
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Laurence
Cornez, Michaël Aupetit et Manuel Samuelides.
Performances et intelligibilité
de deux systèmes de
discrimination appliqués à des données sismiques.
Actes des 38èmes
Journées de Statistiques
(JDS’2006), Clamart, 29 May-2 June 2006.
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JDS
2006
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P. Gaillard, D.
Mercier, M. Aupetit
Etudes des SVM probabilistes pour la discrimination des événements sismiques français
Actes des 38èmes
Journées de Statistiques
(JDS’2006), Clamart, June 2006.
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JDS
2006
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Pierre Gaillard, Michaël Aupetit
Modélisation de la Topologie
avec le Graphe Génératif
Gaussien
Actes des 2èmes Rencontres Inter-Associations, Laboratoire
ERI, Université Lyon 2, 20-21 March 2006.
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RIAs
2006
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Michaël Aupetit
Visualiser les distorsions
dans les techniques de projection continues
Actes du 4e
atelier Visualisation et Extraction de Connaissances de la conférence
EGC, 17 January 2006.
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VEC@
EGC
2006
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2005
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David Mercier, Michaël
Aupetit, Robert Quach,
Jean-Denis Muller
How to help seismic analysts to verify the French
seismic bulletin?
The 9th International
Conference on Engineering Applications of Neural Networks EANN’05, Lille,
24-26 August 2005
http://www.ensm-douai.fr/eann05/
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EANN
2005
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Michaël Aupetit
A Generative Gaussian Graph to learn the topology
of a set of points
Proceedings of the Workshop on Self-Organizing Maps (WSOM’05),
Paris, 5-8 September 2005.
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WSOM
2005
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Roueff, A. Aupetit,
M. Cansi,
Y. Piserchia, P.-F.
Discrimination of events in the Indian Ocean
Proceedings of Oceans 2005 – vol. 2, pp. 1111-1116, 20-23 June 2005
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OCEAN 2005
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2004
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Michaël Aupetit
Visualizing distortions in
continuous projection techniques.
Proc. of European
Symposium on Artificial Neural Networks (ESANN’2004), Bruges, April 2004.
Editor Michel Verleysen, d-side, pp. 465-470.
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ESANN 2004
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M.
Aupetit
Visualiser les distorsions
dans les techniques de projection
Actes des Journées de Statistiques
(JDS’2004), Montpellier, June 2004. http://www.agro-montpellier.fr/sfds/CD/textes.htm
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JDS
2004
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2003
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Michaël Aupetit
Robust Topology Representing Networks
Proc. of European Symposium on Artificial Neural Networks
(ESANN’2003), Bruges, April 2003. Editor M. Verleysen,
d-side, pp. 45-50.
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ESANN 2003
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Michaël Aupetit
High-dimensional labeled
data analysis with Gabriel graphs
Proc. of European Symposium on Artificial Neural Networks
(ESANN’2003), Bruges, April 2003. Editor M. Verleysen,
d-side, pp. 21-26.
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ESANN 2003
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M.
Aupetit
Utilisation des graphes de
proximité pour l’analyse
de données multi-dimensionnelles
étiquetées
Actes des Journées de Statistiques
(JDS’2003),pp. 125-128, Lyon, 2-6 June 2003.
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JDS
2003
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2002
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M.
Aupetit
Voisinage γ-observable et effet
d’auto-répartition
Actes du congrès CAp2002, pp. 99-110, Orléans
17-19 June 2002
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Cap
2002
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2001
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Michaël Aupetit, Pierre Couturier, Pierre Massotte
Vector quantization with y-Observable neighbors
in Allinson N., Hujun Y., Allinson L., Slack J. (eds),
Advances in Self-Organizing Maps. Proceedings WSOM 2001, Lincoln UK,
Springer, pp. 230-237, June 2001
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WSOM
2001
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Michaël Aupetit, Pierre Couturier, Pierre Massotte
Induced Voronoï Kernels
for Principal Manifolds Approximation
in Allinson N., Hujun Y., Allinson L., Slack J. (eds),
Advances in Self-Organizing Maps. Proceedings WSOM 2001, Lincoln UK, Springer,
pp. 75-80, June 2001.
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WSOM
2001
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2000
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Michaël Aupetit, Pierre Couturier, Pierre Massotte
A “Recruiting Neural-Gas” for Function
Approximation
Proc. of the IEEE-INNS-ENNS Int. Joint Conf. on Neural Networks (IJCNN
2000), Vol. 3, pp. 91-96, Como, Italy, July 24-27, 2000
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IJCNN
2000
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M. Aupetit, P. Massotte, P.
Couturier
Function Approximation with Continuous
Self-Organizing Maps using Neighboring Influence
Interpolation
ICSC symposium on neural computation, NC’2000, pp. 247–253,
Berlin, Germany, 26 May 2000
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NC
2000
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2000
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M.
Aupetit, P. Massotte,
P. Couturier
Interpolation multi-dimensionnelle pour l'approximation
de fonction avec les réseaux
de neurones auto-organisants
Actes du 12ème Congrès Francophone AFRIF-AFIA :
Reconnaissance des Formes et Intelligence Artificielle (RFIA 2000), Vol. 3, pp. 397-406, Paris,
February 2000.
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RFIA
2000
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1999
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M. Aupetit, P. Massotte, P.
Couturier
C-SOM : a continuous self-organizing map for
function approximation
Proc. of International Conference Intelligent Systems and Control
(ISC1999), pp. 38-43, Santa Barbara, USA, October 1999
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ISC
1999
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M. Aupetit, P. Massotte, P.
Couturier
A continuous self-organizing map using spline
technique for function approximation
Proc. of AICS'99, pp. 163-169, Cork, Irlande, September 1999.
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AICS
1999
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Invited talks (national/international)
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2012
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Dagstuhl Seminar 12081
Information
Visualization, Visual Data Mining and Machine Learning
https://www.dagstuhl.de/en/program/calendar/semhp/?semnr=12081
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Dagstuhl
12081
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2011
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Brillouin Seminar
Apprentissage de la topologie
de signaux multi-capteurs
Organized by
Thales Research and LIX Ecole Polytechnique
IRCAM Paris
21/10/2011
Video : http://archiprod-externe.ircam.fr/video/VI02019600-178.mp4
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Brillouin
2011
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2010
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Michaël Aupetit et Sylvain Lespinats
La visualisation multidimensionnelle
pour l'analyse exploratoire
de données.
BILAB French seminar on Business Intelligence
(Telecom Paris Tech)
http://bilab.enst.fr/wakka.php?wiki=SeminairE
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BILAB
2010
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2008
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Michaël Aupetit
Analyse exploratoire
de données et approches
topologiques
AAFD French seminar on Machine Learning and Data Mining (LIPN, Univ.
Paris 13)
http://www-lipn.univ-paris13.fr/A3/AAFD08/
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AAFD
2008
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Habilitation for Research Supervision
(HDR)
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2012
|
Michaël Aupetit
Approches topologiques
pour l’analyse exploratoire
de données et l’aide à
la décision
(Topological
approaches for exploratory data analysis and decision support)
11/07/2012 –
Paris Sud 11 University – Paris Saclay Campus
http://fr.slideshare.net/MichaelAupetit/soutenance-hdr-aupetit2012
Mentor
J.-D. Fekete (INRIA Orsay, France);
Reviewers
G. Melançon (LABRI, Univ. Bordeaux, France);
A. Zighed (Univ. Lyon 2, Lyon, France);
M. Verleysen (DICE, Univ. Louvain-la-Neuve,
Belgium);
Jury
M. Sebag (INRIA Orsay, France);
G. Govaert (CNRS Heudiasyc,
Univ. Tech. Compiègne, France) ;
Y. Bennani (LIPN, Univ. Paris 13, France) ;
M. Verleysen (DICE, Univ. Louvain-la-Neuve,
Belgium) ;
J.-D. Fekete (INRIA Orsay,
France);
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French Open Public Event on Artificial Intelligence
|
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2011
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Contribution to 8
posters for AFIA 2011 Open Public Event
http://michael.aupetit.free.fr/Posters_AFIA2011_PublicEvent.htm
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AFIA
2011
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