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\n  \n 2017\n \n \n (1)\n \n \n
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\n  \n Preprint\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n \n Clustering and Model Selection via Penalized Likelihood for Different-sized Categorical Data Vectors.\n \n \n \n \n\n\n \n Derman, E.; and Le Pennec, E.\n\n\n \n\n\n\n Submission. 2017.\n \n\n\n\n
\n\n\n\n \n \n \"Clustering pdf\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n\n\n\n
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@Article{Derman17,\n  author =\t {Derman, E. and Le Pennec, E.},\n  title =\t {Clustering and Model Selection via Penalized\n                  Likelihood for Different-sized Categorical Data\n                  Vectors},\n  journal =\t {Submission},\n  year =\t 2017,\n  lang =\t {English},\n  keywords =\t {Preprint, eGMM, ThemeCond},\n  pubtype =\t {Preprint},\n  subject =\t {eGMM},\n  preprint =\t {eGMM/2017-arXiv-DLP.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Preprint/eGMM/2017-arXiv-DLP.pdf},\n  arXiv =\t {1709.02294}\n}\n\n\n
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\n  \n 2014\n \n \n (1)\n \n \n
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\n  \n Article\n \n \n (2)\n \n \n
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\n \n\n \n \n \n \n \n \n Mixture of Gaussian regressions model with logistic weights, a penalized maximum likelihood approach.\n \n \n \n \n\n\n \n Montuelle, L.; and Le Pennec, E.\n\n\n \n\n\n\n Electron. J. Statist., 8(1): 1661-1695. 2014.\n \n\n\n\n
\n\n\n\n \n \n \"Mixture pdf\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n\n\n\n
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@Article{montuelle12:_condit,\n  author =\t {Montuelle, L. and Le Pennec, E.},\n  title =\t {Mixture of Gaussian regressions model with logistic\n                  weights, a penalized maximum likelihood approach},\n  JOURNAL =\t {Electron. J. Statist.},\n  FJOURNAL =\t {Electronic Journal of Statistics},\n  YEAR =\t 2014,\n  VOLUME =\t 8,\n  NUMBER =\t 1,\n  PAGES =\t {1661-1695},\n  ISSN =\t {1935-7524},\n  DOI =\t\t {10.1214/14-EJS939},\n  SICI =\t {1935-7524(2014)8:1<1661:MOGRMW>2.0.CO;2-8},\n  year =\t 2014,\n  keywords =\t {Article, eGMM, ThemeCond},\n  pubtype =\t {Article},\n  subject =\t {eGMM},\n  lang =\t {English},\n  preprint =\t {eGMM/2014-arXiv-MLP.pdf},\n  reprint =\t {eGMM/2014-EJS-MLP.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/eGMM/2014-EJS-MLP.pdf},\n  reprintok =\t 1,\n  lang =\t {English},\n  hal =\t\t {hal-00809735},\n  arXiv =\t {1304.2696},\n  inriaRR =\t 8281,\n}\n\n
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\n \n\n \n \n \n \n \n \n Unsupervised segmentation of hyperspectral images with spatialized Gaussian mixture model and model selection.\n \n \n \n \n\n\n \n Cohen, S.; and Le Pennec, E.\n\n\n \n\n\n\n OGST, 69(2): 245–260. 2014.\n \n\n\n\n
\n\n\n\n \n \n \"Unsupervised pdf\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n\n\n\n
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@Article{cohen14:unsupseg,\n  author =\t {Cohen, S. and Le Pennec, E.},\n  title =\t {Unsupervised segmentation of hyperspectral images\n                  with spatialized {Gaussian} mixture model and model\n                  selection},\n  journal =\t {OGST},\n  fjournal =\t {Oil & Gas Science and Technology - Revue d'IFP\n                  Energies nouvelles},\n  year =\t 2014,\n  keywords =\t {Article, eGMM, ThemeCond},\n  pubtype =\t {Article},\n  x-editorial-board ={yes},\n  x-international-audience ={yes},\n  pubtype =\t {Article},\n  subject =\t {eGMM},\n  volume =\t 69,\n  number =\t 2,\n  pages =\t {245--260},\n  preprint =\t {eGMM/2014-OGST-CLP.pdf},\n  reprint =\t {eGMM/2014-OGST-CLP.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/eGMM/2014-OGST-CLP.pdf},\n  lang =\t {English},\n  doi =\t\t {10.2516/ogst/2014013},\n  reprintok =\t 1\n}\n\n
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\n  \n 2013\n \n \n (3)\n \n \n
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\n \n\n \n \n \n \n \n \n Régression gaussienne à poids logistiques et maximum de vraisemblance pénalisé.\n \n \n \n \n\n\n \n Montuelle, L.; and Le Pennec, E.\n\n\n \n\n\n\n In Journée de la SFdS, Toulouse, 2013. \n \n\n\n\n
\n\n\n\n \n \n \"Régression pdf\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n\n\n\n
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@InProceedings{MontSfdS13,\n  author =\t {Montuelle, L. and Le Pennec, E.},\n  title =\t {Régression gaussienne à poids logistiques et maximum\n                  de vraisemblance pénalisé},\n  booktitle =\t {Journée de la SFdS},\n  year =\t 2013,\n  address =\t {Toulouse},\n  x-international-audience ={no},\n  x-proceedings ={yes},\n  x-invited-conference ={no},\n  keywords =\t {Actes, eGMM, ThemeCond},\n  pubtype =\t {Actes de conférence nationale},\n  subject =\t {eGMM},\n  preprint =\t {eGMM/2013-SFdS-MLP.pdf},\n  reprint =\t {eGMM/2013-SFdS-MLP.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/eGMM/2013-SFdS-MLP.pdf},\n  reprintok =\t 1,\n  lang =\t {Francais},\n  hal =\t\t {inria-00386668},\n}\n\n%%% 2012\n\n
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\n \n\n \n \n \n \n \n \n Partition-Based Conditional Density Estimation.\n \n \n \n \n\n\n \n Cohen, S.; and Le Pennec, E.\n\n\n \n\n\n\n ESAIM Probab. Stat., 17: 672–697. 2013.\n \n\n\n\n
\n\n\n\n \n \n \"Partition-Based pdf\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@Article{cohen12:_partit_based_condit_densit_estim,\n  author =\t {Cohen, S. and Le Pennec, E.},\n  title =\t {Partition-Based Conditional Density Estimation},\n  journal =\t {ESAIM Probab. Stat.},\n  fjournal =\t {ESAIM Probability and Statistics},\n  year =\t 2013,\n  keywords =\t {Article, eGMM, ThemeCond, ThemeCond},\n  x-editorial-board ={yes},\n  x-international-audience ={yes},\n  pubtype =\t {Article},\n  subject =\t {eGMM},\n  preprint =\t {eGMM/2012-ESAIMPS-CLP.pdf},\n  reprint =\t {eGMM/2013-ESAIMPS-CLP.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/eGMM/2013-ESAIMPS-CLP.pdf},\n  lang =\t {English},\n  volume =\t 17,\n  pages =\t {672--697},\n  doi =\t\t {10.1051/ps/2012017},\n  reprintok =\t 1\n}\n\n
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\n  \n Preprint\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n \n Conditional Density Estimation by Penalized Likelihood Model Selection.\n \n \n \n \n\n\n \n Cohen, S.; and Le Pennec, E.\n\n\n \n\n\n\n Submission. 2013.\n \n\n\n\n
\n\n\n\n \n \n \"Conditional pdf\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n\n\n\n
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@Article{cohen11:_condit_densit_estim_penal_likel_model,\n  author =\t {Cohen, S. and Le Pennec, E.},\n  title =\t {Conditional Density Estimation by Penalized\n                  Likelihood Model Selection},\n  journal =\t {Submission},\n  year =\t 2013,\n  keywords =\t {Preprint, eGMM, ThemeCond},\n  pubtype =\t {Preprint},\n  subject =\t {eGMM},\n  preprint =\t {eGMM/2011-Pre1-CLP.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Preprint/eGMM/2011-Pre1-CLP.pdf},\n  lang =\t {English}\n}\n\n%%% Accepted\n\n%%% 2024\n
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\n \n\n \n \n \n \n \n \n Segmentation non supervisée d'image hyperspectrale par mélange de gausiennes spatialisé.\n \n \n \n \n\n\n \n Cohen, S.; and Le Pennec, E.\n\n\n \n\n\n\n In GRETSI 11, Bordeaux, 2011. \n \n\n\n\n
\n\n\n\n \n \n \"Segmentation pdf\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n\n\n\n
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@InProceedings{cohen11:_segmen,\n  author =\t {Cohen, S. and Le Pennec, E.},\n  title =\t {Segmentation non supervisée d'image hyperspectrale\n                  par mélange de gausiennes spatialisé},\n  booktitle =\t {GRETSI 11},\n  year =\t 2011,\n  address =\t {Bordeaux},\n  x-international-audience ={no},\n  x-proceedings ={yes},\n  x-invited-conference ={no},\n  keywords =\t {Actes, eGMM, ThemeCond},\n  pubtype =\t {Actes de conférence nationale},\n  subject =\t {eGMM},\n  preprint =\t {eGMM/2011-GRETSI-CLP.pdf},\n  reprint =\t {eGMM/2011-GRETSI-CLP.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/eGMM/2011-GRETSI-CLP.pdf},\n  reprintok =\t 1,\n  lang =\t {Francais}\n}\n\n
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\n \n\n \n \n \n \n \n \n European research platform IPANEMA at the SOLEIL synchrotron for ancient and historical materials.\n \n \n \n \n\n\n \n Bertrand, L.; Languille, M.; Cohen, S.; Robinet, L.; Gervais, C.; Leroy, S.; Bernard, D.; Le Pennec, E.; Josse, W.; Doucet, J.; and Schöder, S.\n\n\n \n\n\n\n J. Synchrotron Radiat., 18(5): 765–772. 2011.\n \n\n\n\n
\n\n\n\n \n \n \"European pdf\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n\n\n\n
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@article{bertrand11:_europ_ipanem_soleil,\n  author =\t {Bertrand, L. and Languille, M.-A. and Cohen, S. and\n                  Robinet, L. and Gervais, C. and Leroy, S. and\n                  Bernard, D.  and Le Pennec, E. and Josse, W. and\n                  Doucet, J. and Schöder, S.},\n  title =\t {European research platform {IPANEMA} at the {SOLEIL}\n                  synchrotron for ancient and historical materials},\n  journal =\t {J. Synchrotron Radiat.},\n  fjournal =\t {Journal of Synchrotron Radiation},\n  year =\t 2011,\n  volume =\t 18,\n  number =\t 5,\n  pages =\t {765--772},\n  reprint =\t {eGMM/2011-JSR-BLCRGLBLPJDS.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/eGMM/2011-JSR-BLCRGLBLPJDS.pdf},\n  reprintok =\t 1,\n  x-editorial-board ={yes},\n  x-international-audience ={yes},\n  keywords =\t {Article, eGMM, ThemeCond},\n  pubtype =\t {Article},\n  subject =\t {eGMM},\n  lang =\t {English},\n  doi =\t\t {10.1107/S090904951102334X},\n}\n\n
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\n \n\n \n \n \n \n \n \n Conditional Density Estimation by Penalized Likelihood Model Selection and Applications.\n \n \n \n \n\n\n \n Cohen, S.; and Le Pennec, E.\n\n\n \n\n\n\n Technical Report INRIA, 2011.\n \n\n\n\n
\n\n\n\n \n \n \"Conditional pdf\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n\n\n\n
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@TechReport{cohen11:_condit_densit_estim_penal_selec,\n  author =\t {Cohen, S. and Le Pennec, E.},\n  title =\t {Conditional Density Estimation by Penalized\n                  Likelihood Model Selection and Applications},\n  institution =\t {INRIA},\n  year =\t 2011,\n  keywords =\t {TechReport, eGMM, ThemeCond},\n  pubtype =\t {Technical report},\n  subject =\t {eGMM},\n  preprint =\t {eGMM/2011-arXiv-CLP.pdf},\n  url_PDF = {http://lepennec.perso.math.cnrs.fr/Preprint/eGMM/2011-arXiv-CLP.pdf},\n  lang =\t {English},\n  hal =\t\t {inria-00575462},\n  arXiv =\t {1103.2021},\n  inriaRR =\t 7596\n}\n\n
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