En eet, je suis persuadé que la topologie est au coeur du substrat fondamental à l'émergence de nos processus cognitifs humains, et que la structure de ce substrat est acquise par apprentissage. Il me paraît donc pertinent d'utiliser ce même substrat et son processus de génération automatique dans les machines an d'une part de les rendre aussi intelligentes que nous jugeons l'être, et d'autre part de nous permettre de les comprendre et d'en garder la maîtrise, ne de mieux nous comprendre. Aussi mon programme de recherche s'attache-t-il à explorer cette hypothèse et à en exploiter les résultats ,
Metric graph reconstruction from noisy data, Proceedings of the Annual Symposium on Computational Geometry, p.3746, 2011. ,
Competitive learning algorithms for vector quantization, Neural Networks, vol.3, issue.3, 1990. ,
DOI : 10.1016/0893-6080(90)90071-R
Looking for a good fuzzy system interpretability index: An experimental approach, International Journal of Approximate Reasoning, vol.51, issue.1, p.115134, 2009. ,
DOI : 10.1016/j.ijar.2009.09.004
Conscious robots ,
The Grand Tour: A Tool for Viewing Multidimensional Data, SIAM Journal on Scientific and Statistical Computing, vol.6, issue.1, p.128143, 1985. ,
DOI : 10.1137/0906011
Robust topology representing networks, European Symp. on Articial Neural Networks, p.4550, 2003. ,
Learning topology with the generative gaussian graph and the em algorithm, Advances in Neural Information Processing Systems, pp.8390-98, 2006. ,
Visualizing distortions and recovering topology in continuous projection techniques, Neurocomputing, vol.70, issue.7-9, p.13041330, 2007. ,
DOI : 10.1016/j.neucom.2006.11.018
Nearly homogeneous multi-partitioning with a deterministic generator, Neurocomputing, vol.72, issue.7-9, p.13791389, 2009. ,
DOI : 10.1016/j.neucom.2008.12.024
Winsitu, un nouveau paradigme pour l'analyse exploratoire de données basée sur des projections. Revue des Nouvelles Technologies de l ?Information, A, Apprentissage et Visualisation, issue.41, p.7998, 2010. ,
Winsitu : a new information visualization paradigm for visual mining of multidimensional data. Submitted to Data Mining and Knowledge Discovery special issue on Intelligent Interactive Data Visualization, 2012. ,
Visual analytics to check marine containers in the eritr@c project ,
High-dimensional labeled data analysis with topology representing graphs, Neurocomputing, vol.63, p.139169, 2005. ,
DOI : 10.1016/j.neucom.2004.04.009
Nips workshop on topology learning : New challenges at the crossing of machine learning, computational geometry and topology, 2007. ,
Mesurer et visualiser les distorsions dans les techniques de projection continues. Revue Intelligence Articielle, Visualisation et extraction des connaissances, p.443472, 2008. ,
DOI : 10.3166/ria.22.443-472
The quickhull algorithm for convex hulls, ACM Transactions on Mathematical Software, vol.22, issue.4, p.469483, 1996. ,
DOI : 10.1145/235815.235821
Manifold regularization : A geometric framework for learning from examples, Journal of Machine Learning Research, vol.7, p.23992434, 2006. ,
Learning Deep Architectures for AI, Machine Learning, pp.1127-99, 2009. ,
DOI : 10.1561/2200000006
GraphDice: A System for Exploring Multivariate Social Networks, Computer Graphics Forum, vol.11, issue.6, p.29863872, 2010. ,
DOI : 10.1111/j.1467-8659.2009.01687.x
URL : https://hal.archives-ouvertes.fr/inria-00521661
GTM: The Generative Topographic Mapping, Neural Computation, vol.39, issue.1, p.215234, 1998. ,
DOI : 10.1007/BF01889678
A statistical approach to persistent homology. Homology, homotopy and Applications, p.337362, 2007. ,
Encyclopedia of Human Computer Interaction. Idea group reference edition, 2005. ,
Topology and data, Bulletin of the American Mathematical Society, vol.46, issue.2, p.255308, 2009. ,
DOI : 10.1090/S0273-0979-09-01249-X
A classication em algorithm for clustering and two stochastic versions, Comput. Stat. Data Anal, vol.14, p.315332, 1992. ,
DOI : 10.1016/0167-9473(92)90042-e
URL : https://hal.inria.fr/inria-00075196/document
Persistence-based clustering in riemannian manifolds, Proceedings of the 27th annual ACM symposium on Computational geometry, p.97106, 2011. ,
URL : https://hal.archives-ouvertes.fr/hal-01094872
A taxonomy of visualization techniques using the data state reference model, IEEE Symposium on Information Visualization 2000. INFOVIS 2000. Proceedings, pp.69-75, 2000. ,
DOI : 10.1109/INFVIS.2000.885092
Neuro-Fuzzy Inference System to Learn Expert Decision: Between Performance and Intelligibility, Fuzzy Systems and Knowledge Discovery (FSKD'05), p.12811293, 2005. ,
DOI : 10.1007/11540007_168
Geology of mankind, Nature, issue.6867, p.41523, 2002. ,
Approximations by superpositions of sigmoidal functions, Mathematics of Control, Signals, and Systems, vol.2, issue.4, p.303314, 1989. ,
Self comes to mind, p.100, 2010. ,
Curvilinear component analysis : a self-organising neural network for non-linear mapping of data sets, IEEE Trans. on Neural Networks, vol.8, issue.1, p.148154, 1997. ,
Maximum likelihood from incomplete data via the em algorithm, Journal of the Royal Statistical Society, Series B, vol.39, issue.1, p.138, 1977. ,
Dynamical systems and cognitive linguistics: toward an active morphodynamical semantics, Neural Networks, vol.18, issue.5-6, p.628638, 2005. ,
DOI : 10.1016/j.neunet.2005.06.009
Gabriel meshes and delaunay edge ips, SIAM/ACM Joint Conference on Geometric and Physical Modeling (SPM '09), p.295300, 2009. ,
DOI : 10.1145/1629255.1629293
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.150.8469
Topological persistence and simplication, IEEE Symp. on Found. of Comp. Sci, p.454463, 2000. ,
Triangulating Topological Spaces, International Journal of Computational Geometry and Applications, vol.7, issue.4, p.365378, 1997. ,
DOI : 10.1142/s0218195997000223
From data mining to knowledge discovery in databases, p.3754, 1996. ,
Model-Based Clustering, Discriminant Analysis, and Density Estimation, Journal of the American Statistical Association, vol.97, issue.458, p.611631, 2002. ,
DOI : 10.1198/016214502760047131
Growing Cell Structures ??? a Self-organizing Network in k Dimensions, Articial Neural Networks, p.10511056, 1992. ,
DOI : 10.1016/B978-0-444-89488-5.50047-6
A growing neural gas network learns topologies, Advances in Neural Information Processing Systems, 1995. ,
The estimation of the gradient of a density function, with applications in pattern recognition . Information Theory, IEEE Transactions on, vol.21, issue.1, pp.32-40, 1975. ,
Apprentissage de la connexité dún nuage de points par modèle génératif. applications à lánalyse exploratoire de données et à la classication semi-supervisée, 2008. ,
Learning topology of a labeled data set with the supervised generative Gaussian graph, Neurocomputing, vol.71, issue.7-9, pp.7-912831299, 2008. ,
DOI : 10.1016/j.neucom.2007.12.028
Learning topology of a labeled data set with the supervised generative Gaussian graph, Neurocomputing, vol.71, issue.7-9, pp.71-78, 2008. ,
DOI : 10.1016/j.neucom.2007.12.028
Un graphe génératif pour la classication semi-supervisée. Ingénierie des systèmes d'information, p.97119, 2010. ,
DOI : 10.3166/isi.15.2.97-119
Neural Networks and the Bias/Variance Dilemma, Neural Computation, vol.36, issue.1, p.158, 1992. ,
DOI : 10.1162/neco.1990.2.1.1
The Amsterdam Library of Object Images, International Journal of Computer Vision, vol.61, issue.1, p.103112, 2005. ,
DOI : 10.1023/B:VISI.0000042993.50813.60
The Ecological Approach to Visual Perception, Houghton Miin, 1979. ,
Topological analysis of chaotic dynamical systems, Reviews of Modern Physics, vol.70, issue.4, p.14551530, 1998. ,
DOI : 10.1103/RevModPhys.70.1455
Reconstruction Using Witness Complexes, Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms (SODA '07), pp.1076-1085, 2007. ,
DOI : 10.1007/s00454-008-9094-6
URL : https://hal.archives-ouvertes.fr/hal-00488434
Interactive Visualization of Small World Graphs, IEEE Symposium on Information Visualization, 2004. ,
DOI : 10.1109/INFVIS.2004.43
Principal Curves, Journal of the American Statistical Association, vol.26, issue.406, p.502516, 1989. ,
DOI : 10.1080/03610927508827223
Algebraic Topology, 2001. ,
Neural Networks : A Comprehensive Foundation, 1998. ,
Evaluation of proxiviz for the visual analysis of multidimensional data, 2012. ,
Modeling the manifolds of images of handwritten digits, IEEE Transactions on Neural Networks, vol.8, issue.1, p.6574, 1997. ,
DOI : 10.1109/72.554192
The plane with parallel coordinates. The Visual Computer, p.6991, 1985. ,
Relative neighborhood graphs and their relatives, Proceedings of the IEEE, p.15021517, 1992. ,
DOI : 10.1109/5.163414
Principal Component Analysis, 1986. ,
DOI : 10.1007/978-1-4757-1904-8
Comparing distributions and shapes using the kernel distance, Proceedings of the 27th annual ACM symposium on Computational geometry, SoCG '11, p.4756, 2011. ,
DOI : 10.1145/1998196.1998204
Drawing graphs -methods and models, Lecture Notes in Computer Science, 2001. ,
The discovery of structural form, Proceedings of the National Academy of Sciences, vol.105, issue.31, p.1068710692, 2008. ,
DOI : 10.1073/pnas.0802631105
Special issue : Foundations and frontiers of visual analytics, Information Visualization, vol.8, issue.4, p.239314, 2009. ,
Self-Organization and Associative Memory Formation, 1988. ,
Self-Organizing Maps, Series in Information Sciences, 2001. ,
Self organization of a massive document collection, IEEE Transactions on Neural Networks, vol.11, issue.3, p.574585, 2000. ,
DOI : 10.1109/72.846729
Curvilinear distance analysis versus isomap, Proceedings of the European Symposium on Articial Neural Networks, p.185192, 2002. ,
Nonlinear Dimensionality Reduction, 2007. ,
DOI : 10.1007/978-0-387-39351-3
Locally linear embedding versus isotop, Proceedings of the European Symposium on Articial Neural Network, p.527534, 2003. ,
L'approche écologique de la cognition social et son impact sur la conception des traits de personnalité. L'année psychologique, p.249294, 2004. ,
DOI : 10.3406/psy.2004.29667
Concerning the dierentiability of the energy function in vector quantization algorithms, Neural Networks, vol.20, p.621630, 2007. ,
Classimap : a supervised non-linear mapping which preserves the topology of the classes, 2012. ,
False neighbourhoods and tears are the main mapping defaults. how to avoid it ? how to exhibit remaining ones ? Proceeding of Quality Issues, Measures of Interestingness and Evaluation of data mining models (QI- MIE'09, p.5565, 2009. ,
CheckViz: Sanity Check and Topological Clues for Linear and Non-Linear Mappings, Computer Graphics Forum, vol.11, issue.5, p.113125, 2011. ,
DOI : 10.1111/j.1467-8659.2010.01835.x
DD-HDS: A Method for Visualization and Exploration of High-Dimensional Data, IEEE Transactions on Neural Networks, vol.18, issue.5, pp.1265-1279, 2007. ,
DOI : 10.1109/TNN.2007.891682
URL : https://hal.archives-ouvertes.fr/inserm-00250168
Visualizing highdimensional data using t-sne, Journal of Machine Learning Research, vol.9, p.25792605, 2008. ,
Finite Mixture Models, 2000. ,
Some methods of classication and analysis of multivariate observations, Proceedings of the Fifth Berkeley Symposium on Mathemtical Statistics and Probability, p.281297, 1967. ,
Automating the design of graphical presentations of relational information, ACM Transactions on Graphics, vol.5, issue.2, p.110141, 1986. ,
DOI : 10.1145/22949.22950
On the generalised distance in statistics, Proceedings of the National Institute of Sciences of India, pp.4955-104, 1936. ,
neuralgas network for vector quantization and its application to time-series prediction, IEEE Trans. on NN, vol.4, issue.4, p.558569, 1993. ,
Computing Voronoi Adjacencies in High Dimensional Spaces by Using Linear Programming, Mathematical Methodologies in Pattern Recognition and Machine Learning, vol.30, p.507522, 2013. ,
DOI : 10.1007/978-1-4614-5076-4_3
How to help seismic analysts to verify the French seismic bulletin?, Engineering Applications of Artificial Intelligence, vol.19, issue.7, p.797806, 2006. ,
DOI : 10.1016/j.engappai.2006.05.008
The magical number seven, plus or minus two : Some limits on our capacity for processing information, The Psychological Review, vol.63, issue.2, p.8197, 1956. ,
Andrews curves, Wiley Interdisciplinary Reviews: Computational Statistics, vol.34, issue.4, p.373382, 2011. ,
DOI : 10.1002/wics.160
Elements of Algebraic Topology, 1993. ,
Uci repository of machine learning databases, 1998. ,
Approaches to uncertainty visualization. The Visual Computer, p.370390, 1997. ,
Syntaxe topologique et grammaire cognitive, Langages, vol.25, issue.103, 1991. ,
DOI : 10.3406/lgge.1991.1610
Practical Bayesian Density Estimation Using Mixtures of Normals, Journal of the American Statistical Association, vol.22, issue.439, p.894902, 1997. ,
DOI : 10.1080/01621459.1997.10474044
Learning the 2-d topology of images, 2007. ,
URL : https://hal.archives-ouvertes.fr/inria-00176067
Learning Interpretable Models, p.105, 2006. ,
A Nonlinear Mapping for Data Structure Analysis, IEEE Transactions on Computers, vol.18, issue.5, p.401409, 1969. ,
DOI : 10.1109/T-C.1969.222678
Advances in Kernel Methods : Support Vector Learning, 1999. ,
The Design Space of Implicit Hierarchy Visualization: A Survey, IEEE Transactions on Visualization and Computer Graphics, vol.17, issue.4, p.393411, 2011. ,
DOI : 10.1109/TVCG.2010.79
Estimating the Dimension of a Model, The Annals of Statistics, vol.6, issue.2, p.461464, 1978. ,
DOI : 10.1214/aos/1176344136
Topological estimation using witness complexes, Eurographics Symposium on Point-Based Graphics, p.157166, 2004. ,
Plex : Simplicial complexes in matlab, 2003. ,
Global versus local methods for nonlinear dimensionality reduction, Advances in Neural Information Processing Systems, p.705712, 2003. ,
Density Estimation for Statistics and Data Analysis, 1998. ,
DOI : 10.1007/978-1-4899-3324-9
A tutorial on support vector regression, Statistics and Computing, vol.14, issue.3, 2004. ,
DOI : 10.1023/B:STCO.0000035301.49549.88
An Integrated Laboratory Robotic System for Autonomous Discovery of Gene Function, Journal of the Association for Laboratory Automation, vol.15, issue.1, p.3340, 2010. ,
DOI : 10.1016/j.jala.2009.10.001
Principal curves revisited, Statistics and Computing, vol.11, issue.4, p.183190, 1992. ,
DOI : 10.1007/BF01889678
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.57.5261
Sparse bayesian learning and the relevance vector machine, J. Mach. Learn. Res, vol.1, p.211244, 0106. ,
Multidimensional scaling i -theory and methods . Psychometrica, C. Touzet. Conscience, intelligence, vol.17115, p.401419, 1952. ,
Exploratory Data Analysis, 1977. ,
Information retrieval perspective to nonlinear dimensionality reduction for data visualization, Journal of Machine Learning Research, vol.11, p.451490, 2010. ,
A new quantitative measure of topology preservation in Kohonen's feature maps, Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94), p.645648, 1994. ,
DOI : 10.1109/ICNN.1994.374251
Information Visualization : Perception for Design, 2004. ,
Cushion treemaps: visualization of hierarchical information, Proceedings 1999 IEEE Symposium on Information Visualization (InfoVis'99), p.7378, 1999. ,
DOI : 10.1109/INFVIS.1999.801860
The Grammar of Graphics, 2005. ,
Topology representing network for sensor-based robot motion planning, World Congress on Neural Networks, p.100103, 1996. ,
A statistical approach to class separability, Applied Stochastic Models in Business and Industry, vol.65, issue.2, p.187197, 2005. ,
DOI : 10.1002/asmb.532
Topology for Computing, 2005. ,
DOI : 10.1017/CBO9780511546945