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\n \n\n \n \n \n \n \n \n Real-time diagnosis aid method and decision-support for medical diagnosis to a user of a medical system .\n \n \n \n \n\n\n \n Allassonnière, S.; Besson, R.; and Le Pennec, E.\n\n\n \n\n\n\n 2024.\n \n\n\n\n
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@Patent{allassonniere21,\n  author =\t {Allassonnière, S. and Besson, R. and Le Pennec, E.},\n  title =\t {Real-time diagnosis aid method and decision-support for medical diagnosis to a user of a medical system },\n  year =\t 2024,\n  number =\t {US11881309B2},\n  keywords =\t {Patent, TOP5, Health, ThemeHealth, RL, ThemeRL},\n  subject =\t {Health, RL},\n  pubtype =\t {Patent},\n  reprint =\t {Patent/2021-ABLP.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/Patent/2024-ABLP.pdf},\n  reprintok =\t 1,\n  lang =\t {English}\n}\n\n
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\n \n\n \n \n \n \n \n \n Towards Minimax Optimality of Model-based Robust Reinforcement Learning.\n \n \n \n \n\n\n \n Clavier, P.; Le Pennec, E.; and Geist, M.\n\n\n \n\n\n\n In Conference on Uncertainty in Artificial Intelligence (UAI), 2024. \n \n\n\n\n
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@inproceedings{clavier24,\n  author          = {Clavier, P. and Le Pennec, E. and Geist, M.},\n  booktitle       = {Conference on Uncertainty in Artificial Intelligence (UAI)},\n  title           = {Towards Minimax Optimality of Model-based Robust Reinforcement Learning},\n  year            = {2024},\n   keywords =\t {Proceedings, RL, ThemeRL},\n  pubtype =\t {Proceedings of international conference},\n  subject =\t {RL},\n   url_pdf = {http://lepennec.perso.math.cnrs.fr/Preprint/RL/2024-UAI-CLPG},\n  lang = {english}\n}\n\n\n
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\n \n\n \n \n \n \n \n \n Progressive State Space Disaggregation for Infinite Horizon Dynamic Programming.\n \n \n \n \n\n\n \n Forghieri, O.; Castel, H.; Hyon, E.; and Le Pennec, E.\n\n\n \n\n\n\n In International Conference on Automated Planning and Scheduling, 2024. \n \n\n\n\n
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@inproceedings{Forghieri24,\n  author          = {Forghieri, O. and Castel, H. and Hyon, E. and Le Pennec, E.},\n  booktitle       = {International Conference on Automated Planning and Scheduling},\n  title           = {Progressive State Space Disaggregation for Infinite Horizon Dynamic Programming},\n  year            = {2024},\n  keywords =\t {Proceedings, RL, ThemeRL},\n  pubtype =\t {Proceedings of international conference},\n  subject =\t {RL},\n  url_pdf = {http://lepennec.perso.math.cnrs.fr/Preprint/RL/2024-ICAPS-FCHLP.pdf},\n  lang = {english}\n}\n\n%%% 2023\n\n
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\n \n\n \n \n \n \n \n \n Un algorithme multiéchelle pour déformer les objets de façon réaliste - application à la modélisation de la croissance du cerveau foetal.\n \n \n \n \n\n\n \n Gaudfernau, F. A.; and Le Pennec, E.\n\n\n \n\n\n\n In GRETSI, 2023. \n \n\n\n\n
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@inproceedings{gaudfernau23b,\n  author          = {Gaudfernau, F. Allassonière, S. and Le Pennec, E.},\n  booktitle       = {GRETSI},\n  title           = {Un algorithme multiéchelle pour déformer les objets de façon réaliste - application à la modélisation de la croissance du cerveau foetal},\n  year            = {2023},\n  keywords =\t {Actes, Health, ThemeHealth},\n  pubtype =\t {Actes de conférence nationale},\n  subject =\t {Health},\n    url_pdf = {http://lepennec.perso.math.cnrs.fr/Preprint/Health/2023-GRETSI-GALP.pdf},\n  lang = {fr}\n}\n\n
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\n \n\n \n \n \n \n \n \n Development and clinical validation of real-time artificial intelligence diagnostic companion for fetal ultrasound examination.\n \n \n \n \n\n\n \n Stirnemann, J.; Besson, R.; Spaggiari, E.; Rojo, S.; Loge, F.; Peyro-Saint-Paul, H.; Allassonniere, S.; Le Pennec, E.; Hutchinson, C.; Sebire, N.; and Ville, Y.\n\n\n \n\n\n\n Ultrasound in Obstetrics & Gynecology, 3(62): 353-360. 2023.\n \n\n\n\n
\n\n\n\n \n \n \"Development 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 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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@article{stirnemann23,\n  author          = {Stirnemann, J. and Besson, R. and Spaggiari, E.  and Rojo, S. and Loge, F. and Peyro-Saint-Paul, H. and Allassonniere, S. and Le Pennec, E. and Hutchinson, C. and Sebire, N.J. and Ville, Y.},\n  journal         = {Ultrasound in Obstetrics \\& Gynecology},\n  number          = {62},\n  title           = {Development and clinical validation of real-time artificial intelligence diagnostic companion for fetal ultrasound examination},\n  volume          = {3},\n  year            = {2023},\n  pages           = {353-360},\n  keywords =\t {Article, Health, ThemeHealth},\n  pubtype =\t {Article},\n  subject =\t {Health},\n  doi = {10.1002/uog.26242},\n  lang = {english},\n  url_pdf = {http://lepennec.perso.math.cnrs.fr/Reprint/Health/2023-UOG-SBSBRLPPALPHSV.pdf},\n}\n\n
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\n \n\n \n \n \n \n \n \n Procédé de contrôle d'un système et produit programme d'ordinateur associé.\n \n \n \n \n\n\n \n Dhaou, A.; Bertoncello, A.; Gourvenec, S.; Garnier, J.; and Le Pennec, E.\n\n\n \n\n\n\n 2023.\n \n\n\n\n
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@Patent{Dhaou23p,\n  author =\t {Dhaou, A. and Bertoncello, A. and Gourvenec, S. and Garnier, J. and Le Pennec, E.},\n  title =\t {Procédé de contrôle d'un système et produit programme d'ordinateur associé},\n  year =\t 2023,\n  number =\t {FR3124868B1},\n  keywords =\t {Patent, Causality, ThemeCausality},\n  pubtype =\t {Patent},\n  theme = {Causality},\n  reprint =\t {Patent/2023-DBGGLP.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/Patent/2023-DBGGLP.pdf},\n  reprintok =\t 1,\n  lang =\t {Français}\n}\n\n
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\n \n\n \n \n \n \n \n \n Procédé de synthèse d'images.\n \n \n \n \n\n\n \n Prenat, M.; Le Pennec, E.; and Berginc, G.\n\n\n \n\n\n\n 2023.\n \n\n\n\n
\n\n\n\n \n \n \"Procédé 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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@Patent{Prenat19,\n  author =\t {Prenat, M. and Le Pennec, E. and Berginc, G.},\n  title =\t {Procédé de synthèse d'images},\n  year =\t 2023,\n  number =\t {FR/3075438B1},\n  keywords =\t {Patent, Detection, ThemeDetection},\n  pubtype =\t {Patent},\n  theme = {Detection},\n  reprint =\t {Patent/2019-PLP.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/Patent/2023-PLPG.pdf},\n  reprintok =\t 1,\n  lang =\t {Français}\n}\n\n
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\n \n\n \n \n \n \n \n \n Input uncertainty propagation through trained neural networks.\n \n \n \n \n\n\n \n Monchot, P.; Coquelin, L.; Petit, S.; Marmin, S.; Le Pennec, E.; and Fischer, N.\n\n\n \n\n\n\n In International Conference on Machine Learning, 2023. \n \n\n\n\n
\n\n\n\n \n \n \"Input 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{monchot23,\n  author          = {Monchot, P. and Coquelin, L. and Petit, S. and Marmin, S. and Le Pennec, E. and Fischer, N.},\n  booktitle       = {International Conference on Machine Learning},\n  title           = {Input uncertainty propagation through trained neural networks},\n  year            = {2023},\n  keywords =\t {Proceedings, Causality, ThemeCausality},\n  pubtype =\t {Proceedings of international conference},\n  subject =\t {Causality},\n    url_pdf = {http://lepennec.perso.math.cnrs.fr/Preprint/Causality/2023-ICML-MCPMLP.pdf},\n  lang = {english}\n}\n\n
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\n \n\n \n \n \n \n \n \n A multiscale algorithm for computing realistic image transformations - Application to the modelling of fetal brain growth.\n \n \n \n \n\n\n \n Gaudfernau, F.; Allassonnière, S.; and Le Pennec, E.\n\n\n \n\n\n\n In SPIE Medical Imaging, 2023. \n \n\n\n\n
\n\n\n\n \n \n \"A 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{gaudfernau23,\n  author          = {Gaudfernau, F. and Allassonnière, S. and Le Pennec, E.},\n  booktitle       = {SPIE Medical Imaging},\n  title           = {A multiscale algorithm for computing realistic image transformations - Application to the modelling of fetal brain growth},\n  year            = {2023},\n  keywords =\t {Proceedings, Health, ThemeHealth},\n  pubtype =\t {Proceedings of international conference},\n  subject =\t {Health},\n  url_pdf = {http://lepennec.perso.math.cnrs.fr/Preprint/Health/2023-SPIE-GALP.pdf},\n  lang = {english}\n}\n\n%%% 2022\n\n
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\n \n\n \n \n \n \n \n \n Robust Reinforcement Learning with Distributional Risk-averse formulation.\n \n \n \n \n\n\n \n Clavier, P.; Allassonnière, S.; and Le Pennec, E.\n\n\n \n\n\n\n arXiv. 2022.\n \n\n\n\n
\n\n\n\n \n \n \"Robust 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
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@article{clavier22,\n  author          = {Clavier, P. and Allassonnière, S. and Le Pennec, E.},\n  journal         = {arXiv},\n  title           = {Robust Reinforcement Learning with Distributional Risk-averse formulation},\n  year            = {2022},\n  pubtype =\t {Preprint},\n  keywords =\t {Preprint, RL},\n  pubtype =\t {Preprint},\n  subject =\t {RL},\n  url_pdf = {http://lepennec.perso.math.cnrs.fr/Preprint/RL/2022-arXiv-CALP},\n  arXiv = {2206.06841}\n}\n
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\n \n\n \n \n \n \n \n \n Wavelet-Based Multiscale Initial Flow For Improved Atlas Estimation in the Large Diffeomorphic Deformation Model Framework.\n \n \n \n \n\n\n \n Gaudfernau, F.; Blondiaux, E.; Allassonnière, S.; and Le Pennec, E.\n\n\n \n\n\n\n arXiv. 2022.\n \n\n\n\n
\n\n\n\n \n \n \"Wavelet-Based 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{gaudfernau22,\n  author          = {Gaudfernau, F. and Blondiaux, E. and Allassonnière, S. and Le Pennec, E.},\n  journal         = {arXiv},\n  title           = {Wavelet-Based Multiscale Initial Flow For Improved Atlas Estimation in the Large Diffeomorphic Deformation Model Framework},\n  year            = {2022},\n  lang =\t {English},\n  pubtype =\t {Preprint},\n  keywords =\t {Preprint, Health, ThemeHealth},\n  pubtype =\t {Preprint},\n  subject =\t {Health},\n  url_pdf = {http://lepennec.perso.math.cnrs.fr/Preprint/Health/2022-HAL-GBALP.pdf},\n  arXiv = {2206.06841}\n}\n\n% @article {stirnemann21m,\n% \tauthor = {Stirnemann, J. and Besson, R. and Spaggiari, E. and Bourgon, N. and Rojo, S. and Loge, F. and Peyro-Saint-Paul, H. and Allassonniere, S. and Le Pennec, E. and Ville, Y.},\n% \ttitle = {Description and clinical validation of a real-time AI diagnostic companion for fetal ultrasound examination},\n% \telocation-id = {2021.05.25.21257630},\n% \tyear = {2021},\n% \tdoi = {10.1101/2021.05.25.21257630},\n% \tpublisher = {Cold Spring Harbor Laboratory Press},\n% \tabstract = {Objective To describe a real-time decision support system (DSS), named SONIO, to assist ultrasound-based prenatal diagnosis and to assess its performance using a clinical database of precisely phenotyped postmortem examinations.Population and Methods This DSS is knowledge-based and comprises a dedicated thesaurus of 294 syndromes and diseases. It operates by suggesting, at each step of the ultrasound examination, the best next symptom to check for in order to optimize the diagnostic pathway to the smallest number of possible diagnoses. This assistant was tested on a single-center database of 251 cases of postmortem phenotypes with a definite diagnosis. Adjudication of discordant diagnoses was made by a panel of external experts. The primary outcome was a target concordance rate \\&gt;90\\% between the postmortem diagnosis and the top-7 diagnoses given by SONIO when providing the full phenotype as input. Secondary outcomes included concordance for the top-5 and top-3 diagnoses; We also assessed a {\\textquotedblleft}1-by-1{\\textquotedblright} model, providing only the anomalies sequentially prompted by the system, mimicking the use of the software in a real-life clinical setting.Results The validation database covered 96 of the 294 (32.65\\%) syndromes and 79\\% of their overall prevalence in the SONIO thesaurus. The adjudicators discarded 42/251 cases as they were not amenable to ultrasound based diagnosis. SONIO failed to make the diagnosis on 7/209 cases. On average, each case displayed 6 anomalies, 3 of which were considered atypical for the condition. Using the {\\textquoteleft}full-phenotype{\\textquoteright} model, the success rate of the top-7 output of Sonio was 96.7\\% (202/209). This was 91.9\\% and 87.1\\% for the top-5 and top-3 outputs respectively. Using the {\\textquotedblleft}1-by-1{\\textquotedblright} model, the correct diagnosis was within the top-7, top-5 and top-3 of SONIO{\\textquoteright}s output in 72.4\\%, 69.3\\% and 63.1\\%.Conclusion Sonio is a robust DSS with a success-rate \\&gt;95\\% for top-7 ranking diagnoses when the full phenotype is provided, using a large database of noisy real data. The success rate over 70\\% using the {\\textquoteleft}1-by-1{\\textquoteright} model was understandably lower, given that SONIO{\\textquoteright}s sequential queries may not systematically cover the full phenotype.Competing Interest StatementJS, RB, ES, SA, ELP and YV are co-founders of the SONIO company. SR, FLM and HPSP are employed by the SONIO company.Clinical TrialThis was a retrospective observational study from clinical recordsFunding StatementNo fundingAuthor DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:This study was approved by the local ethics committee of the Necker hospital (IRB registration : CERPAHP.5 $\\#$00011928)All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesThe validation data will be made partly available, upon request. The algorithms and thesaurus of the SONIO DSS are the property of the SONIO company},\n% \t% URL = {https://www.medrxiv.org/content/early/2021/05/25/2021.05.25.21257630},\n%   % eprint = {https://www.medrxiv.org/content/early/2021/05/25/2021.05.25.21257630.full.pdf},\n%   url_pdf = {http://lepennec.perso.math.cnrs.fr/Reprint/Health/2021-medRxiv-SBSBRLPSPALPV.pdf},\n% \tjournal = {medRxiv},\n%   lang =\t {English},\n%   pubtype =\t {Preprint},\n%   keywords =\t {Preprint, Health, ThemeHealth, RL, ThemeRL},\n%   pubtype =\t {Preprint},\n%   subject =\t {Health, RL},\n%   hal =\t\t {hal-03620367v1}\n% }\n\n
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\n \n\n \n \n \n \n \n \n Clinical validation of a real‐time AI diagnostic companion for fetal ultrasound examination.\n \n \n \n \n\n\n \n Stirnemann, J.; Besson, R.; Spaggiari, E.; Rojo, S.; Loge, F.; Peyro-Saint-Paul, H.; Allassonniere, S.; Le Pennec, E.; Hutchinson, C.; Sebire, N.; and Ville, Y.\n\n\n \n\n\n\n In volume 60, pages 14-15, 2022. \n \n\n\n\n
\n\n\n\n \n \n \"Clinical 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 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{stirnemann22,\n  author          = {Stirnemann, J. and Besson, R. and Spaggiari, E.  and Rojo, S. and Loge, F. and Peyro-Saint-Paul, H. and Allassonniere, S. and Le Pennec, E. and Hutchinson, C. and Sebire, N.J. and Ville, Y.},\ntitle = {Clinical validation of a real‐time AI diagnostic companion for fetal ultrasound examination},\nboktitle = {Ultrasound in Obstetrics \\& Gynecology},\nvolume = {60},\npages = {14-15},\nkeywords =\t {Proceedings, Health, ThemeHealth},\n  pubtype =\t {Proceedings of international conference},\n  subject =\t {Health},\ndoi = {10.1002/uog.26242},\nurl_pdf = {http://lepennec.perso.math.cnrs.fr/Reprint/Health/2022-UOG-SBSBRLPPALPHSV.pdf},\nyear = {2022},\n  lang =\t {English}\n}\n\n%%% 2021\n\n
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\n  \n Article\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n \n Intelligent Questionnaires Using Approximate Dynamic Programming.\n \n \n \n \n\n\n \n Logé, F.; Le Pennec, E.; and Amadou-Boubacar, H.\n\n\n \n\n\n\n i-com, 19(3): 227-237. 2021.\n \n\n\n\n
\n\n\n\n \n \n \"Intelligent 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 \n\n\n\n
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@Article{Loge21,\n  author          = {Logé, F. and Le Pennec, E. and Amadou-Boubacar, H.},\n  title           = {Intelligent Questionnaires Using Approximate Dynamic Programming},\n  journal       = {i-com},\n  year            = {2021},\n  keywords =\t {Article, Health, ThemeHealth, TOP5, RL, ThemeRL},\n  pubtype =\t {Article},\n  subject =\t {Health, RL},\n  volume = 19,\n  number = 3,\n  pages = {227-237},\n  doi = {doi/10.1515/icom-2020-0022},\n  %preprint = {RL/2020-LLPAB-UCAI.pdf},\n  reprint = {RL/2021-LLPAB-i-com.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/RL/2021-LLPAB-i-com.pdf},\n  reprintOK = 1,\n  lang =\t {English}\n}\n\n
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\n  \n Proceedings of international conference\n \n \n (2)\n \n \n
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\n \n\n \n \n \n \n \n \n Causal and Interpretable Rules for Time Series Analysis.\n \n \n \n \n\n\n \n Dhaou, A.; Bertoncello, A.; Gourvénec, S.; Garnier, J.; and Le Pennec, E.\n\n\n \n\n\n\n In Knowledge Discovery and Data Mining, pages 2764–2772, 2021. \n \n\n\n\n
\n\n\n\n \n \n \"Causal 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 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{Dhaou21,\n  author          = {Dhaou, A. and Bertoncello, A. and Gourvénec, S. and Garnier, J. and Le Pennec, E.},\n  title           = {Causal and Interpretable Rules for Time Series Analysis},\n  booktitle       = {Knowledge Discovery and Data Mining},\n  year            = {2021},\n  doi             = {doi/10.1145/3447548.3467161},\n  pubtype =\t {Proceedings of international conference},\n  keywords =\t {Proceedings, Causality, ThemeCausality},\n  x-international-audience ={yes},\n  x-proceedings ={yes},\n  subject = {Causality},\n  x-invited-conference ={no},\n  pages = {2764–2772},\n  url_PDF = {http://lepennec.perso.math.cnrs.fr/Reprint/Causality/2021-KDD-DBGGLP.pdf},\n  lang =\t {English}\n}\n\n
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\n \n\n \n \n \n \n \n \n Description and clinical validation of a real-time AI diagnostic companion for fetal ultrasound examination.\n \n \n \n \n\n\n \n Stirnemann, J.; Besson, R.; Spaggiari, E.; Bourgon, N.; Rojo, S.; Loge, F.; Peyro-Saint-Paul, H.; Allassonniere, S.; Le Pennec, E.; and Ville, Y.\n\n\n \n\n\n\n In Ultrasound in Obstetrics & Gynecology, volume 58, pages 169-170, 2021. \n \n\n\n\n
\n\n\n\n \n \n \"Description 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 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{stirnemann21,\n  author          = {Stirnemann, J. and Besson, R. and Spaggiari, E. and Bourgon, N. and Rojo, S. and Loge, F. and Peyro-Saint-Paul, H. and Allassonniere, S. and Le Pennec, E. and Ville, Y.},\ntitle = {Description and clinical validation of a real-time AI diagnostic companion for fetal ultrasound examination},\nbooktitle = {Ultrasound in Obstetrics \\& Gynecology},\nvolume = {58},\nnumber = {S1},\npages = {169-170},\nkeywords =\t {Proceedings, Health, ThemeHealth},\n  pubtype =\t {Proceedings of international conference},\n  subject =\t {Health},\ndoi = {10.1002/uog.24291},\n%url = {https://obgyn.onlinelibrary.wiley.com/doi/abs/10.1002/uog.24291},\n%eprint = {https://obgyn.onlinelibrary.wiley.com/doi/pdf/10.1002/uog.24291},\nurl_pdf = {http://lepennec.perso.math.cnrs.fr/Reprint/Health/2021-UOG-SBSBRLPSPALPV.pdf},\nyear = {2021},\n  lang =\t {English}\n}\n\n%%% 2020\n
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\n \n\n \n \n \n \n \n \n Challenging common bolus advisor for self-monitoring type-I diabetes patients using Reinforcement Learning.\n \n \n \n \n\n\n \n Logé, F.; Le Pennec, E.; and Amadou-Boubacar, H.\n\n\n \n\n\n\n In 2020 KDD Workshop on Applied Data Science for Healthcare, 2020. \n \n\n\n\n
\n\n\n\n \n \n \"Challenging 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 \n \n \n\n\n\n
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@inproceedings{LogeDSHealh20,\n  author          = {Logé, F. and Le Pennec, E. and Amadou-Boubacar, H.},\n  title           = {Challenging common bolus advisor for self-monitoring type-I diabetes patients using Reinforcement Learning},\n  booktitle       = {2020 KDD Workshop on Applied Data Science for Healthcare},\n  year            = {2020},\n  keywords =\t {Proceedings, Health, ThemeHealth, TOP5, RL, ThemeRL},\n  pubtype =\t {Proceedings of international conference},\n  subject =\t {Health, RL},\n  x-international-audience ={yes},\n  x-proceedings ={yes},\n  x-invited-conference ={no},\n  preprint = {RL/2020-LLPAB-DSHealth.pdf},\n  reprint = {RL/2020-LLPAB-DSHealth.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/RL/2020-LLPAB-DSHealth.pdf},\n  arxiv = {2007.11880},\n  reprintOK = 1,\n  lang =\t {English}\n}\n\n
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\n \n\n \n \n \n \n \n \n Adaptive predictive-questionnaire by approximate dynamic programming.\n \n \n \n \n\n\n \n Logé, F.; Le Pennec, E.; and Amadou-Boubacar, H.\n\n\n \n\n\n\n In UCAI 2020, 2020. \n \n\n\n\n
\n\n\n\n \n \n \"Adaptive 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{LogeUCAI20,\n  author          = {Logé, F. and Le Pennec, E. and Amadou-Boubacar, H.},\n  title           = {Adaptive predictive-questionnaire\nby approximate dynamic programming},\n  booktitle       = {UCAI 2020},\n  year            = {2020},\n  keywords =\t {Proceedings, RL, ThemeRL},\n  pubtype =\t {Proceedings of international conference},\n  subject =\t {RL},\n  x-international-audience ={yes},\n  x-proceedings ={yes},\n  x-invited-conference ={no},\n  preprint = {RL/2020-LLPAB-UCAI.pdf},\n  reprint = {RL/2020-LLPAB-UCAI.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/RL/2020-LLPAB-UCAI.pdf},\n  reprintOK = 1,\n  lang =\t {English}\n}\n\n
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\n \n\n \n \n \n \n \n \n Optimization of a Sequential Decision Making Problem for a Rare Disease Diagnostic Application.\n \n \n \n \n\n\n \n Besson, R.; Le Pennec, E.; Allassonnière, S.; Stirnemann, J.; Neuraz, A.; and Spaggiari, E.\n\n\n \n\n\n\n In ICAART 2020, 2020. \n \n\n\n\n
\n\n\n\n \n \n \"Optimization 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 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 \n \n \n\n\n\n
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@InProceedings{BessonIcaart20,\n  author =\t {Besson, R. and Le Pennec, E. and Allassonnière,\n                  S. and Stirnemann, J. and Neuraz, A. and Spaggiari,\n                  E.},\n  title =\t {Optimization of a Sequential Decision Making Problem for a Rare Disease Diagnostic Application},\n  year =\t 2020,\n  booktitle =\t {ICAART 2020},\n  keywords =\t {Proceedings, Health, ThemeHealth, TOP5, RL, ThemeRL},\n  pubtype =\t {Proceedings of international conference},\n  subject =\t {Health, RL},\n  x-international-audience ={yes},\n  x-proceedings ={yes},\n  x-invited-conference ={no},\n  preprint = {RL/2020-BLPSNSA-ICAART.pdf},\n  reprint = {RL/2020-BLPSNSA-ICAART.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/RL/2020-BLPSNSA-ICAART.pdf},\n  reprintOK = 1,\n  lang =\t {English},\n  doi = {10.5220/0008938804750482}\n}\n\n%%% 2019\n\n\n
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\n \n\n \n \n \n \n \n \n Learning from both experts and data.\n \n \n \n \n\n\n \n Besson, R.; Le Pennec, E.; and Allassonnière, S.\n\n\n \n\n\n\n Entropy, 12(1). 2019.\n \n\n\n\n
\n\n\n\n \n \n \"Learning 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{Besson19,\n  author =\t {Besson, R. and Le Pennec, E. and Allassonnière, S.},\n  title =\t {Learning from both experts and data},\n  journal =\t {Entropy},\n  year =\t 2019,\n  keywords =\t {Article, RL, ThemeRL},\n  pubtype =\t {Article},\n  subject =\t {RL},\n  volume =\t 12,\n  number =\t 1,\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/RL/2019-Entropy-BLPA.pdf},\n  preprint =\t {RL/2019-arXiv-BLPA.pdf},\n  reprint =\t {RL/2019-Entropy-BLPA.pdf},\n  reprintok =\t 1,\n  lang =\t {English},\n  arXiv =\t {1910.09043},\n  doi =\t\t {10.3390/e21121208}\n}\n\n
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\n \n\n \n \n \n \n \n \n Automatic detection of Interplanetary Coronal Mass Ejections from in-situ data: a deep learning approach.\n \n \n \n \n\n\n \n Nguyen, G.; Aunai, N.; Fontaine, D.; Le Pennec, E.; Vandenbossche, J.; Jeandet, A.; Bakkali, B.; Vignoli, L.; and Refaldo-Saint Blancard, B.\n\n\n \n\n\n\n The Astrophysical Journal. 2019.\n \n\n\n\n
\n\n\n\n \n \n \"Automatic 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{nguyen19:_autom_inter_coron_mass_eject,\n  author =\t {Nguyen, G. and Aunai, N. and Fontaine, D. and Le\n                  Pennec, E. and Vandenbossche, J. and Jeandet, A. and\n                  Bakkali, B. and Vignoli, L. and Refaldo-Saint\n                  Blancard, B.},\n  title =\t {Automatic detection of Interplanetary Coronal Mass\n                  Ejections from in-situ data: a deep learning\n                  approach},\n  journal =\t {The Astrophysical Journal},\n  year =\t 2019,\n  lang =\t {English},\n  subject =\t {Detection},\n  pubtype =\t {Article},\n  keywords =\t {Article, Detection, ThemeTarget},\n  arxiv =\t {1903.10780},\n  preprint =\t {Detection/2019-arXiv-NAFLPVJBVR.pdf},\n  reprint =\t {Detection/2019-Astro-NAFLPVJBVR.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/Detection/2019-Astro-NAFLPVJBVR.pdf},\n  reprintok =\t 1,\n  doi =\t\t {10.3847/1538-4357/ab0d24}\n}\n\n
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\n \n\n \n \n \n \n \n \n PAC-Bayesian aggregation of linear estimators.\n \n \n \n \n\n\n \n Montuelle, L.; and Le Pennec, E.\n\n\n \n\n\n\n Nonparametric Statistics. 2019.\n \n\n\n\n
\n\n\n\n \n \n \"PAC-Bayesian 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{montuelle18:_pac,\n  author =\t {Montuelle, L. and Le Pennec, E.},\n  title =\t {PAC-Bayesian aggregation of linear estimators},\n  journal =\t {Nonparametric Statistics},\n  year =\t 2019,\n  page =\t {133-144},\n  lang =\t {English},\n  keywords =\t {Article, eGMM, ThemeAggreg},\n  pubtype =\t {Article},\n  subject =\t {Aggregation},\n  preprint =\t {Aggregation/2018-arXiv-MLP.pdf},\n  reprint =\t {Aggregation/2019-NPS-MLP.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/Aggregation/2019-NPS-MLP.pdf},\n  reprintok =\t 1,\n  arXiv =\t {1410.0661},\n  doi =\t\t {10.1007/978-3-319-96941-1_9}\n}\n\n\n
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\n  \n Proceedings of international conference\n \n \n (2)\n \n \n
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\n \n\n \n \n \n \n \n \n Energy Management for Microgrids: a Reinforcement Learning Approach.\n \n \n \n \n\n\n \n Levent, T.; Preux, P.; Le Pennec, E.; Badosa, J.; Henri, G.; and Bonnassieux, Y.\n\n\n \n\n\n\n In IEE ISGT Europe, 2019. \n \n\n\n\n
\n\n\n\n \n \n \"Energy 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 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{Levent19,\n  author =\t {Levent, T. and Preux, Ph. and Le Pennec, E. and\n                  Badosa, J. and Henri, G. and Bonnassieux, Y.},\n  title =\t {Energy Management for Microgrids: a Reinforcement\n                  Learning Approach},\n  booktitle =\t {IEE ISGT Europe},\n  year =\t 2019,\n  x-international-audience ={yes},\n  x-proceedings ={yes},\n  x-invited-conference ={no},\n  keywords =\t {Proceedings, RL, TOP5},\n  pubtype =\t {Proceedings of international conference},\n  subject =\t {RL},\n  preprint =\t {RL/2019-ISGT-LPLPBHB.pdf},\n  reprint =\t {RL/2019-ISGT-LPLPBHB.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/RL/2019-ISGT-LPLPBHB.pdf},\n  reprintok =\t 1,\n  lang =\t {English},\n  doi =\t\t {10.1109/ISGTEurope.2019.8905538}\n}\n\n
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\n \n\n \n \n \n \n \n \n Representation Of Polysomnography Recordings As Low Dimensional Trajectories .\n \n \n \n \n\n\n \n Solelhac, G.; Brigham, M.; Bouchequet, P.; Andrillon, T.; Chennaoui, M.; Le Pennec, E.; Rey, M.; and Léger, D.\n\n\n \n\n\n\n In Sleep, volume 42, pages A128, 2019. \n 33rd Annual Meeting of the Associated Professional Sleep Societies\n\n\n\n
\n\n\n\n \n \n \"Representation 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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@InProceedings{Solelhac19,\n  author =\t {Solelhac, G. and Brigham, M. and\n                  Bouchequet, P. and Andrillon, Th. and\n\t\t  Chennaoui, M. and Le Pennec, E. and Rey, M. and Léger, D.},\n  title =\t {Representation Of Polysomnography Recordings As Low Dimensional Trajectories },\n  booktitle =\t {Sleep},\n  volume =\t 42,\n  pages =\t {A128},\n  year =\t 2019,\n  note =         {33rd Annual Meeting of the Associated Professional Sleep Societies}, \n  doi =\t\t {10.1093/sleep/zsz067.314},\n  x-international-audience ={no},\n  x-proceedings ={yes},\n  x-invited-conference ={no},\n  keywords =\t {Proceedings, Health, ThemeHealth},\n  pubtype =\t {Proceedings of international conference},\n  subject =\t {Health},\n  preprint =\t {Health/2019-Sleep-SBBACLPRL},\n  reprint =\t {Health/2019-Sleep-SBBACLPRL.pdf},\n  reprintok =\t 1,\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/Health/2019-Slepp-SBBACLPRL.pdf},\n  lang =\t {English}\n}\n\n%%% 2018\n\n
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\n \n\n \n \n \n \n \n \n Une nouvelle représentation de la polysomnographie par une technique de machine learning nonsupervisée.\n \n \n \n \n\n\n \n Solelhac, G.; Brigham, M.; Marini, C.; Bouchequet, P.; Chennaoui, M.; Le Pennec, E.; and Léger, D.\n\n\n \n\n\n\n In Médecine du Sommeil, volume 15, pages 49, 2018. \n Résumés du Congrès du Sommeil. Marseille, 23-25 novembre 2017\n\n\n\n
\n\n\n\n \n \n \"Une 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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@InProceedings{Solelhac18nouvelle,\n  author =\t {Solelhac, G. and Brigham, M. and Marini, C. and\n                  Bouchequet, P. and Chennaoui, M. and Le Pennec,\n                  E. and Léger, D.},\n  title =\t {Une nouvelle représentation de la polysomnographie\n                  par une technique de machine learning nonsupervisée},\n  booktitle =\t {Médecine du Sommeil},\n  volume =\t 15,\n  number =\t 1,\n  pages =\t 49,\n  year =\t 2018,\n  note =\t "Résumés du Congrès du Sommeil. Marseille, 23-25\n                  novembre 2017",\n  issn =\t "1769-4493",\n  doi =\t\t "10.1016/j.msom.2018.01.132",\n  x-international-audience ={no},\n  x-proceedings ={yes},\n  x-invited-conference ={no},\n  keywords =\t {Actes, Health, ThemeHealth},\n  pubtype =\t {Actes de conférence nationale},\n  subject =\t {Health},\n  preprint =\t {Health/2017-Sommeil-SBMBCLPL.pdf},\n  reprint =\t {Health/2017-Sommeil-SBMBCLPL.pdf},\n  reprintok =\t 1,\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/Health/2017-Sommeil-SBMBCLPL.pdf},\n  lang =\t {Français}\n}\n\n
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\n \n\n \n \n \n \n \n \n Adaptive Estimation in the Nonparametric Random Coefficients Binary Choice Model by Needlet Thresholding.\n \n \n \n \n\n\n \n Gautier, E.; and Le Pennec, E.\n\n\n \n\n\n\n EJS, 12. 2018.\n \n\n\n\n
\n\n\n\n \n \n \"Adaptive 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{gautier16:_adapt_estim_nonpar_random_coeff,\n  author =\t {Gautier, E. and Le Pennec, E.},\n  title =\t {Adaptive Estimation in the Nonparametric Random\n                  Coefficients Binary Choice Model by Needlet\n                  Thresholding},\n  journal =\t {EJS},\n  year =\t 2018,\n  volume =\t 12,\n  nummber =\t 1,\n  page =\t {277-320},\n  doi =\t\t {10.1214/17-EJS1383},\n  SICI =\t {1935-7524(2018)12:1<277:AEITNR>2.0.CO;2-U},\n  keywords =\t {Article, Needlet, ThemeNeedlet},\n  pubtype =\t {Article},\n  subject =\t {Needlet},\n  preprint =\t {Needlet/2017-arXiv-GLP.pdf},\n  reprint =\t {Needlet/2018-EJS-GLP.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/Needlet/2018-EJS-GLP.pdf},\n  reprintok =\t 1,\n  lang =\t {English},\n  hal =\t\t {inria-00601274},\n  arXiv =\t {1106.3503},\n  inriaRR =\t 7647,\n}\n\n\n\n%%% 2017\n\n
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\n \n\n \n \n \n \n \n \n R pour la statistique et la science des données.\n \n \n \n \n\n\n \n Cornillon, P.; Guyader, A.; Husson, F.; Jégou, N.; Josse, J.; Klutchnikoff, N.; Le Pennec, E.; Matzner-Løber, E.; Rouvière, L.; and Thieurmel, B.\n\n\n \n\n\n\n PUR, 2018.\n \n\n\n\n
\n\n\n\n \n \n \"R 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
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@Book{cornillon18:_r,\n  title =\t {R pour la statistique et la science des données},\n  year =\t 2018,\n  author =\t {Cornillon, P.-A. and Guyader, A. and Husson, F.  and\n                  Jégou, N. and Josse, J. and Klutchnikoff, N. and Le\n                  Pennec, E. and Matzner-Løber, E. and Rouvière,\n                  L. and Thieurmel, B.},\n  publisher =\t {PUR},\n  isbn =\t {978-2-7535-7573-8},\n  lang =\t {Francais},\n  keywords =\t {Book, R},\n  pubtype =\t {Book},\n  preprint =\t {R/2018-R.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Preprint/R/2018-R.pdf},\n}\n\n
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\n  \n Preprint\n \n \n (3)\n \n \n
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\n \n\n \n \n \n \n \n \n A Model-Based Reinforcement Learning Approach for a Rare Disease Diagnostic Task.\n \n \n \n \n\n\n \n Besson, R.; Le Pennec, E.; Allassonnière, S.; Stirnemann, J.; Spaggiari, E.; and Neuraz, A.\n\n\n \n\n\n\n . 2018.\n \n\n\n\n
\n\n\n\n \n \n \"A 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 \n\n\n\n
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@Article{Besson18,\n  author =\t {Besson, R. and Le Pennec, E. and Allassonnière,\n                  S. and Stirnemann, J. and Spaggiari, E. and Neuraz,\n                  A.},\n  title =\t {A Model-Based Reinforcement Learning Approach for a\n                  Rare Disease Diagnostic Task},\n  journaltitle = {Preprint},\n  year =\t 2018,\n  keywords =\t {Preprint, Health, ThemeHealth, RL, ThemeRL},\n  pubtype =\t {Preprint},\n  subject =\t {Health, RL},\n  preprint =\t {Health/2018-arXiv-BLPASSN.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Preprint/Health/2018-arXiv-BLPASSN.pdf},\n  lang =\t {English},\n  arXiv =\t {1811.10112}\n}\n\n
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\n \n\n \n \n \n \n \n \n Fractional-order variational numerical methods for tomographic reconstruction of binary images .\n \n \n \n \n\n\n \n Bergounioux, M.; Le Pennec, E.; and Trélat, E.\n\n\n \n\n\n\n Preprint. 2018.\n \n\n\n\n
\n\n\n\n \n \n \"Fractional-order 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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@Article{Bergounioux18,\n  author =\t {Bergounioux, M. and Le Pennec, E. and Trélat, E.},\n  title =\t {Fractional-order variational numerical methods for\n                  tomographic reconstruction of binary images },\n  journal =\t {Preprint},\n  year =\t 2018,\n  lang =\t {English},\n  keywords =\t {Preprint, Needlet, ThemeNeedlet},\n  pubtype =\t {Preprint},\n  subject =\t {Needlet},\n  preprint =\t {Needlet/2018-HAL-BLPT.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Preprint/Needlet/2018-HAL-BLPT.pdf},\n  hal =\t\t {hal-01794224}\n}\n\n
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\n \n\n \n \n \n \n \n \n Variational Methods for Tomographic Reconstruction with Few Views.\n \n \n \n \n\n\n \n Bergounioux, M.; Abraham, I.; Abraham, R.; Carlier, G.; Le Pennec, E.; and Trélat, E.\n\n\n \n\n\n\n . 2018.\n \n\n\n\n
\n\n\n\n \n \n \"Variational 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{bergounioux18:_variat_method_tomog_recon_few_views,\n  author =\t {Bergounioux, M. and Abraham, I. and Abraham, R. and\n                  Carlier, G.  and Le Pennec, E. and Trélat, E.},\n  title =\t {Variational Methods for Tomographic Reconstruction\n                  with Few Views},\n  journaltitle = {Milan Journal of Mathematics},\n  year =\t 2018,\n  doi =\t\t {10.1007/s00032-018-0285-1},\n  lang =\t {English},\n  keywords =\t {Article, Needlet, ThemeNeedlet},\n  pubtype =\t {Preprint},\n  subject =\t {Needlet},\n  preprint =\t {Needlet/2018-arXiv-BAACLPT.pdf},\n  reprint =\t {Needlet/2018-Milan-BAACLPT.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/Needlet/2018-Milan-BAACLPT.pdf},\n  reprintOK =\t 1\n}\n\n
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\n  \n Actes de conférence nationale\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n \n Optimisation d'arbre de décision pour un problème de détection précoce d'anomalies foetales.\n \n \n \n \n\n\n \n Besson, R.; Le Pennec, E.; and Allassonière, S.\n\n\n \n\n\n\n In Journée de la SFdS, Avignon, 2017. \n \n\n\n\n
\n\n\n\n \n \n \"Optimisation 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{BessonSfdS17,\n  author =\t {Besson, R. and Le Pennec, E. and Allassonière, S.},\n  title =\t {Optimisation d'arbre de décision pour un problème de\n                  détection précoce d'anomalies foetales},\n  booktitle =\t {Journée de la SFdS},\n  year =\t 2017,\n  address =\t {Avignon},\n  x-international-audience ={no},\n  x-proceedings ={yes},\n  x-invited-conference ={no},\n  keywords =\t {Actes, Health, ThemeHealth},\n  pubtype =\t {Actes de conférence nationale},\n  subject =\t {Health},\n  preprint =\t {Health/2017-SFdS-BLPA.pdf},\n  reprint =\t {Health/2017-SFdS-BLPA.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/Health/2017-SFdS-BLPA.pdf},\n  reprintok =\t 1,\n  lang =\t {Francais},\n}\n\n\n%%% 2015\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\n \n \n \n \n \n \n Détection automatique de cibles sous-résolues.\n \n \n \n \n\n\n \n Thivin, S.; Le Pennec, E.; and Prenat, M.\n\n\n \n\n\n\n In Journée de la SFdS, Lille, 2015. \n \n\n\n\n
\n\n\n\n \n \n \"Détection 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{ThivSfdS15,\n  author =\t {Thivin, S. and Le Pennec, E. and Prenat, M.},\n  title =\t {Détection automatique de cibles sous-résolues},\n  booktitle =\t {Journée de la SFdS},\n  year =\t 2015,\n  address =\t {Lille},\n  x-international-audience ={no},\n  x-proceedings ={yes},\n  x-invited-conference ={no},\n  keywords =\t {Actes, Detection, ThemeTarget},\n  pubtype =\t {Actes de conférence nationale},\n  subject =\t {Detection},\n  preprint =\t {Detection/2015-SFdS-TLPP.pdf},\n  reprint =\t {Detection/2015-SFdS-TLPP.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/Detection/2015-SFdS-TLPP.pdf},\n  reprintok =\t 1,\n  lang =\t {Francais},\n}\n\n\n%%% 2014\n\n
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\n  \n Actes de conférence nationale\n \n \n (2)\n \n \n
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\n \n\n \n \n \n \n \n \n Agrégation PAC-bayésienne d'estimateurs par projection.\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, Rennes, 2014. \n \n\n\n\n
\n\n\n\n \n \n \"Agrégation 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{MontSfdS14,\n  author =\t {Montuelle, L. and Le Pennec, E.},\n  title =\t {Agrégation PAC-bayésienne d'estimateurs par\n                  projection},\n  booktitle =\t {Journée de la SFdS},\n  year =\t 2014,\n  address =\t {Rennes},\n  x-international-audience ={no},\n  x-proceedings ={yes},\n  x-invited-conference ={no},\n  keywords =\t {Actes, Aggregation, ThemeAggreg},\n  pubtype =\t {Actes de conférence nationale},\n  subject =\t {Aggregation},\n  preprint =\t {Aggregation/2014-SFdS-MLP.pdf},\n  reprint =\t {Aggregation/2014-SFdS-MLP.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/Aggregation/2014-SFdS-MLP.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 Détection de cibles dans des textures complexes, une approche par segmentation d'images en zones stationnaires.\n \n \n \n \n\n\n \n Thivin, S.; Le Pennec, E.; and Prenat, M.\n\n\n \n\n\n\n In Journée de la SFdS, Rennes, 2014. \n \n\n\n\n
\n\n\n\n \n \n \"Détection pdf\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 4 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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@InProceedings{ThivSfdS14,\n  author =\t {Thivin, S. and Le Pennec, E. and Prenat, M.},\n  title =\t {Détection de cibles dans des textures complexes, une\n                  approche par segmentation d'images en zones\n                  stationnaires},\n  booktitle =\t {Journée de la SFdS},\n  year =\t 2014,\n  address =\t {Rennes},\n  x-international-audience ={no},\n  x-proceedings ={yes},\n  x-invited-conference ={no},\n  keywords =\t {Actes, Detection, ThemeTarget},\n  pubtype =\t {Actes de conférence nationale},\n  subject =\t {Detection},\n  preprint =\t {Detection/2014-SFdS-TLPP.pdf},\n  reprint =\t {Detection/2014-SFdS-TLPP.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/Detection/2014-SFdS-TLPP.pdf},\n  reprintok =\t 1,\n  lang =\t {Francais},\n}\n\n%%% 2013\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 (4)\n \n \n
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\n  \n Actes de conférence nationale\n \n \n (1)\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\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 Adaptive Estimation in the Nonparametric Random Coefficients Binary Choice Model by Needlet Thresholding (extended version).\n \n \n \n \n\n\n \n Gautier, E.; and Le Pennec, E.\n\n\n \n\n\n\n Technical Report Inria, 2013.\n \n\n\n\n
\n\n\n\n \n \n \"Adaptive 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{gautier11:_adapt_estim_nonpar_random_coeff,\n  author =\t {Gautier, E. and Le Pennec, E.},\n  title =\t {Adaptive Estimation in the Nonparametric Random\n                  Coefficients Binary Choice Model by Needlet\n                  Thresholding (extended version)},\n  institution =\t {Inria},\n  year =\t 2013,\n  keywords =\t {TechReport, Needlet, ThemeNeedlet},\n  pubtype =\t {Technical report},\n  subject =\t {Needlet},\n  preprint =\t {Needlet/2011-arXiv-GLP.pdf},\n  url_PDF = {http://lepennec.perso.math.cnrs.fr/Preprint/Needlet/2011-arXiv-GLP.pdf},\n  lang =\t {English},\n  hal =\t\t {inria-00601274v1},\n  arXiv =\t {1106.3503},\n  inriaRR =\t 7647\n}\n\n
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\n  \n 2012\n \n \n (1)\n \n \n
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\n  \n Article\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n \n Radon needlet thresholding.\n \n \n \n \n\n\n \n Kerkyacharian, G.; Le Pennec, E.; and Picard, D.\n\n\n \n\n\n\n Bernoulli, 18(2): 391–433. 2012.\n \n\n\n\n
\n\n\n\n \n \n \"Radon 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{kerkyachaian10:_radon,\n  author =\t {Kerkyacharian, G. and Le Pennec, E. and Picard, D.},\n  title =\t {Radon needlet thresholding},\n  journal =\t {Bernoulli},\n  fjournal =\t {Bernoulli},\n  year =\t 2012,\n  volume =\t 18,\n  number =\t 2,\n  pages =\t {391--433},\n  x-editorial-board ={yes},\n  x-international-audience ={yes},\n  keywords =\t {Article, Needlet, ThemeNeedlet},\n  pubtype =\t {Article},\n  subject =\t {Needlet},\n  preprint =\t {Needlet/2010-Bernoulli-KLPP.pdf},\n  reprint =\t {Needlet/2012-Bernoulli-KLPP.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/Needlet/2012-Bernoulli-KLPP.pdf},\n  reprintok =\t 1,\n  lang =\t {English},\n  hal =\t\t {hal-00409903},\n  arXiv =\t {0908.2514},\n  doi =\t\t {10.3150/10-BEJ340},\n}\n\n%%% 2011\n\n
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\n  \n 2011\n \n \n (3)\n \n \n
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\n  \n Actes de conférence nationale\n \n \n (1)\n \n \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 Article\n \n \n (3)\n \n \n
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\n \n\n \n \n \n \n \n \n Bandlet Image Estimation with Model Selection.\n \n \n \n \n\n\n \n Dossal, C.; Le Pennec, E.; and Mallat, S.\n\n\n \n\n\n\n Sig. Process., 91(12): 2743–2753. 2011.\n \n\n\n\n
\n\n\n\n \n \n \"Bandlet 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 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\n\n
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@Article{dossal11:_bandel_image_estim_model_selec,\n  author =\t {Dossal, Ch. and Le Pennec, E. and Mallat, S.},\n  title =\t {Bandlet Image Estimation with Model Selection},\n  journal =\t {Sig. Process.},\n  fjournal =\t {Signal Processing},\n  year =\t 2011,\n  volume =\t 91,\n  number =\t 12,\n  pages =\t {2743--2753},\n  x-editorial-board ={yes},\n  x-international-audience ={yes},\n  keywords =\t {Article, Bandlets, TOP10, ThemeBandlet},\n  pubtype =\t {Article},\n  subject =\t {Bandlets},\n  preprint =\t {Bandlets/2011-SigPro-DLPM.pdf},\n  reprint =\t {Bandlets/2011-SigPro-DLPM.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/Bandlets/2011-SigPro-DLPM.pdf},\n  reprintok =\t 1,\n  lang =\t {English},\n  hal =\t\t {hal-00321965},\n  arXiv =\t {0809.3092},\n  doi =\t\t {10.1016/j.sigpro.2011.01.013},\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 Adaptive Dantzig density estimation.\n \n \n \n \n\n\n \n Bertin, K.; Le Pennec, E.; and Rivoirard, V.\n\n\n \n\n\n\n Ann. Inst. H. Poincaré Probab. Statist., 47(1): 43–74. 2011.\n \n\n\n\n
\n\n\n\n \n \n \"Adaptive 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{bertin10:_adapt_dantiz,\n  author =\t {Bertin, K. and Le Pennec, E. and Rivoirard, V.},\n  title =\t {Adaptive {Dantzig} density estimation},\n  journal =\t {Ann. Inst. H. Poincaré Probab. Statist.},\n  fjournal =\t {Annales de l'Institut Henri Poincarré. Probabilités\n                  et Statistiques},\n  year =\t 2011,\n  volume =\t 47,\n  number =\t 1,\n  pages =\t {43--74},\n  x-editorial-board ={yes},\n  x-international-audience ={yes},\n  keywords =\t {Article, L1, ThemeDantzig},\n  pubtype =\t {Article},\n  subject =\t {L1},\n  preprint =\t {L1/2011-AIHPB-BLPR.pdf},\n  reprint =\t {L1/2011-AIHPB-BLPR.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/L1/2011-AIHPB-BLPR.pdf},\n  reprintok =\t 1,\n  lang =\t {English},\n  hal =\t\t {hal-00381984},\n  arXiv =\t {0905.0884},\n  doi =\t\t {10.1214/09-AIHP351}\n}\n\n%%% 2010\n\n
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\n  \n Technical report\n \n \n (1)\n \n \n
\n
\n \n \n
\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
\n
@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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\n  \n 2010\n \n \n (1)\n \n \n
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\n  \n Article\n \n \n (3)\n \n \n
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\n \n \n
\n \n\n \n \n \n \n \n \n Inversion of noisy Radon transform by SVD based needlets.\n \n \n \n \n\n\n \n Kerkyacharian, G.; Kyriazis, G.; Le Pennec, E.; Petrushev, P.; and Picard, D.\n\n\n \n\n\n\n Appl. Comput. Harmon. Anal., 28(1): 24–45. 2010.\n \n\n\n\n
\n\n\n\n \n \n \"Inversion 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 {kerkyacharian10:_inver_radon_svd,\n  AUTHOR =\t {Kerkyacharian, G. and Kyriazis, G. and Le Pennec,\n                  E. and Petrushev, P. and Picard, D.},\n  TITLE =\t {Inversion of noisy {Radon} transform by SVD based\n                  needlets},\n  JOURNAL =\t {Appl. Comput. Harmon. Anal.},\n  FJOURNAL =\t {Applied and Computational Harmonic Analysis},\n  YEAR =\t 2010,\n  VOLUME =\t 28,\n  NUMBER =\t 1,\n  PAGES =\t {24--45},\n  x-editorial-board ={yes},\n  x-international-audience ={yes},\n  keywords =\t {Article, Needlet, TOP10,ThemeNeedlet},\n  pubtype =\t {Article},\n  subject =\t {Needlet},\n  preprint =\t {Needlet/2010-ACHA-KKLPPP.pdf},\n  reprint =\t {Needlet/2010-ACHA-KKLPPP.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/Needlet/2010-ACHA-KKLPPP.pdf},\n  reprintok =\t 1,\n  lang =\t {English},\n  hal =\t\t {hal-00321894},\n  arXiv =\t {0809.3332},\n  doi =\t\t {10.1016/j.acha.2009.06.001},\n}\n\n
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\n \n\n \n \n \n \n \n \n Maxisets for Model Selection.\n \n \n \n \n\n\n \n Autin, F.; Le Pennec, E.; Loubes, J.; and Rivoirard, V.\n\n\n \n\n\n\n Constr. Approx., 31(2): 195–229. 2010.\n \n\n\n\n
\n\n\n\n \n \n \"Maxisets 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 {autin10:_maxis_model_selec_estim,\n  AUTHOR =\t {Autin, F. and Le Pennec, E. and Loubes, J.-M. and\n                  Rivoirard, V.},\n  TITLE =\t {Maxisets for Model Selection},\n  JOURNAL =\t {Constr. Approx.},\n  FJOURNAL =\t {Constructive Approximation},\n  YEAR =\t 2010,\n  VOLUME =\t 31,\n  NUMBER =\t 2,\n  PAGES =\t {195--229},\n  x-editorial-board ={yes},\n  x-international-audience ={yes},\n  keywords =\t {Article, Maxiset, ThemeMaxiset},\n  pubtype =\t {Article},\n  subject =\t {Maxiset},\n  preprint =\t {Maxiset/2010-CA-ALPLR.pdf},\n  reprint =\t {Maxiset/2010-CA-ALPLR.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/Maxiset/2010-CA-ALPLR.pdf},\n  reprintok =\t 1,\n  lang =\t {English},\n  hal =\t\t {hal-00259253},\n  arXiv =\t {0802.4192},\n  doi =\t\t {10.1007/s00365-009-9062-2}\n}\n\n
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\n \n\n \n \n \n \n \n \n Thresholding methods to estimate the copula density.\n \n \n \n \n\n\n \n Autin, F.; Le Pennec, E.; and Tribouley, K.\n\n\n \n\n\n\n J. Multivariate Anal., 101(1): 200–222. 2010.\n \n\n\n\n
\n\n\n\n \n \n \"Thresholding 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 {autin10:_thres,\n  AUTHOR =\t {Autin, F. and Le Pennec, E. and Tribouley, K.},\n  TITLE =\t {Thresholding methods to estimate the copula density},\n  JOURNAL =\t {J. Multivariate Anal.},\n  FJOURNAL =\t {Journal of Multivariate Analysis},\n  YEAR =\t 2010,\n  VOLUME =\t 101,\n  NUMBER =\t 1,\n  PAGES =\t {200--222},\n  x-editorial-board ={yes},\n  x-international-audience ={yes},\n  keywords =\t {Article, Copula, TOP10,ThemeCopula},\n  pubtype =\t {Article},\n  subject =\t {Copula},\n  preprint =\t {Copula/2010-JMVA-ALPT.pdf},\n  reprint =\t {Copula/2010-JMVA-ALPT.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/Copula/2010-JMVA-ALPT.pdf},\n  reprintok =\t 1,\n  lang =\t {English},\n  hal =\t\t {hal-00256197},\n  arXiv =\t {0802.2424},\n  doi =\t\t {10.1016/j.jmva.2009.07.009},\n}\n\n%%% 2009\n\n
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\n  \n Actes de conférence nationale\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n \n Agrégation d'estimateurs pour le débruitage d'image.\n \n \n \n \n\n\n \n Le Pennec, E.; and Salmon, J.\n\n\n \n\n\n\n In Journée de la SFdS, Bordeaux, 2009. \n \n\n\n\n
\n\n\n\n \n \n \"Agrégation 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{le09:_agreg,\n  author =\t {Le Pennec, E. and Salmon, J.},\n  title =\t {Agrégation d'estimateurs pour le débruitage d'image},\n  booktitle =\t {Journée de la SFdS},\n  year =\t 2009,\n  address =\t {Bordeaux},\n  x-international-audience ={no},\n  x-proceedings ={yes},\n  x-invited-conference ={no},\n  keywords =\t {Actes, NL-Means, ThemeBandlet},\n  pubtype =\t {Actes de conférence nationale},\n  subject =\t {NL-Means},\n  preprint =\t {NL-Means/2009-Sfds-SLP.pdf},\n  reprint =\t {NL-Means/2009-Sfds-SLP.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/NL-Means/2009-Sfds-SLP.pdf},\n  reprintok =\t 1,\n  lang =\t {Francais},\n  hal =\t\t {inria-00386668},\n}\n\n%%% 2008\n\n
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\n \n\n \n \n \n \n \n \n NL-Means and aggregation procedures.\n \n \n \n \n\n\n \n Salmon, J.; and Le Pennec, E.\n\n\n \n\n\n\n In ICIP 09, pages 2977–2980, 2009. \n \n\n\n\n
\n\n\n\n \n \n \"NL-Means 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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@InProceedings{salmon09:_nl_means,\n  author =\t {Salmon, J. and Le Pennec, E.},\n  title =\t {{NL-Means} and aggregation procedures},\n  booktitle =\t {ICIP 09},\n  pages =\t {2977--2980},\n  year =\t 2009,\n  adress =\t {Cairo},\n  x-international-audience ={yes},\n  x-proceedings ={yes},\n  x-invited-conference ={no},\n  keywords =\t {Proceedings, NL-Means, ThemeAggreg},\n  pubtype =\t {Proceedings of international conference},\n  subject =\t {NL-Means},\n  preprint =\t {NL-Means/2009-ICIP-SLP.pdf},\n  reprint =\t {NL-Means/2009-ICIP-SLP.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/NL-Means/2009-ICIP-SLP.pdf},\n  reprintok =\t 1,\n  lang =\t {English},\n  doi =\t\t {10.1109/ICIP.2009.5414512}\n}\n\n
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\n \n\n \n \n \n \n \n \n An aggregator point of view on NL-Means.\n \n \n \n \n\n\n \n Le Pennec, E.; and Salmon, J.\n\n\n \n\n\n\n In SPIE Wavelet XIII 09, San Diego, 2009. \n \n\n\n\n
\n\n\n\n \n \n \"An 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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@InProceedings{le09:_nl_means,\n  author =\t {Le Pennec, E. and Salmon, J.},\n  title =\t {An aggregator point of view on {NL-Means}},\n  booktitle =\t {SPIE Wavelet XIII 09},\n  year =\t 2009,\n  address =\t {San Diego},\n  x-international-audience ={yes},\n  x-proceedings ={yes},\n  x-invited-conference ={no},\n  keywords =\t {Proceedings, NL-Means, ThemeAggreg},\n  pubtype =\t {Proceedings of international conference},\n  subject =\t {NL-Means},\n  preprint =\t {NL-Means/2009-SPIE-LPS.pdf},\n  reprint =\t {NL-Means/2009-SPIE-LPS.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/NL-Means/2009-SPIE-LPS.pdf},\n  reprintok =\t 1,\n  lang =\t {English},\n  doi =\t\t {10.1117/12.826881}\n}\n\n
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\n \n\n \n \n \n \n \n \n Thresholding methods to estimate the copula density.\n \n \n \n \n\n\n \n Autin, F.; Le Pennec, E.; and Tribouley, K.\n\n\n \n\n\n\n Technical Report LPMA, 2008.\n Extended version arXiv:0802.2424\n\n\n\n
\n\n\n\n \n \n \"Thresholding 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
@TechReport{autin08:_thres,\n  author =\t {Autin, F. and Le Pennec, E. and Tribouley, K.},\n  title =\t {Thresholding methods to estimate the copula density},\n  institution =\t {LPMA},\n  note =\t {Extended version arXiv:0802.2424},\n  year =\t 2008,\n  keywords =\t {TechReport, Copula},\n  pubtype =\t {Technical report},\n  subject =\t {Copula},\n  preprint =\t {Copula/2008-arXiv-ALPT.pdf},\n  url_PDF = {http://lepennec.perso.math.cnrs.fr/Preprint/Copula/2008-arXiv-ALPT.pdf},\n  lang =\t {English},\n  arXiv =\t {0802.2424},\n}\n\n%%% 2007\n\n
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\n  \n 2007\n \n \n (2)\n \n \n
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\n  \n Actes de conférence nationale\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n \n Débruitage géométrique d'image dans des bases orthonormées de bandelettes.\n \n \n \n \n\n\n \n Le Pennec, E.; Dossal, C.; Peyré, G.; and Mallat, S.\n\n\n \n\n\n\n In GRETSI 07, Troyes, 2007. \n \n\n\n\n
\n\n\n\n \n \n \"Débruitage 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{dossal07:_debruit,\n  author =\t {Le Pennec, E. and Dossal, Ch. and Peyré, G. and\n                  Mallat, S. },\n  title =\t {Débruitage géométrique d'image dans des bases\n                  orthonormées de bandelettes},\n  booktitle =\t {GRETSI 07},\n  year =\t 2007,\n  address =\t {Troyes},\n  x-international-audience ={no},\n  x-proceedings ={yes},\n  x-invited-conference ={no},\n  keywords =\t {Actes, Bandlets, ThemeBandlet},\n  pubtype =\t {Actes de conférence nationale},\n  subject =\t {Bandlets},\n  preprint =\t {Bandlets/2007-GRETSI-LPDPM.pdf},\n  reprint =\t {Bandlets/2007-GRETSI-LPDPM.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/Bandlets/2007-GRETSI-LPDPM.pdf},\n  reprintok =\t 1,\n  lang =\t {Francais},\n  hal =\t\t {hal-00365965},\n}\n\n%%% 2006\n\n%%% 2005\n\n
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\n  \n Proceedings of international conference\n \n \n (1)\n \n \n
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\n \n \n
\n \n\n \n \n \n \n \n \n Geometrical Image Estimation with Orthogonal Bandlets Bases.\n \n \n \n \n\n\n \n Peyré, G.; Le Pennec, E.; Dossal, C.; and Mallat, S.\n\n\n \n\n\n\n In SPIE Wavelet XII 07, San Diego, 2007. \n \n\n\n\n
\n\n\n\n \n \n \"Geometrical 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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@InProceedings{dossal07:_geomet_image_estim_orthog_bandl_bases,\n  author =\t {Peyré, G. and Le Pennec, E. and Dossal, Ch. and\n                  Mallat, S. },\n  title =\t {Geometrical Image Estimation with Orthogonal\n                  Bandlets Bases},\n  booktitle =\t {SPIE Wavelet XII 07},\n  year =\t 2007,\n  address =\t {San Diego},\n  x-international-audience ={yes},\n  x-proceedings ={yes},\n  x-invited-conference ={no},\n  keywords =\t {Proceedings, Bandlets, ThemeBandlet},\n  pubtype =\t {Proceedings of international conference},\n  subject =\t {Bandlets},\n  preprint =\t {Bandlets/2007-SPIE-PLPDM.pdf},\n  reprint =\t {Bandlets/2007-SPIE-PLPDM.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/Bandlets/2007-SPIE-PLPDM.pdf},\n  reprintok =\t 1,\n  lang =\t {English},\n  hal =\t\t {hal-00365606},\n  doi =\t\t {10.1117/12.731227}\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 Sparse Geometrical Image Representation with Bandelets.\n \n \n \n \n\n\n \n Le Pennec, E.; and Mallat, S.\n\n\n \n\n\n\n IEEE Trans. Image Process., 14(4): 423–438. 2005.\n \n\n\n\n
\n\n\n\n \n \n \"Sparse 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
@Article{le05:_spars_geomet_image_repres_bandel,\n  author =\t {Le Pennec, E. and Mallat, S.},\n  title =\t {Sparse Geometrical Image Representation with\n                  Bandelets},\n  journal =\t {IEEE Trans. Image Process.},\n  fjournal =\t {IEEE Transactions on Image Processing},\n  year =\t 2005,\n  volume =\t 14,\n  number =\t 4,\n  pages =\t {423--438},\n  x-editorial-board ={yes},\n  x-international-audience ={yes},\n  keywords =\t {Article, Bandlets, ThemeBandlet},\n  pubtype =\t {Article},\n  subject =\t {Bandlets},\n  preprint =\t {Bandlets/2005-IEEE_TIP-LPM.pdf},\n  reprint =\t {Bandlets/2005-IEEE_TIP-LPM.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/Bandlets/2005-IEEE_TIP-LPM.pdf},\n  reprintok =\t 1,\n  lang =\t {English},\n  doi =\t\t {10.1109/TIP.2005.843753},\n}\n\n
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\n\n\n
\n \n\n \n \n \n \n \n \n Bandelet Image Approximation and Compression.\n \n \n \n \n\n\n \n Le Pennec, E.; and Mallat, S.\n\n\n \n\n\n\n Multiscale Model. Sim., 4(3): 992–1039. 2005.\n \n\n\n\n
\n\n\n\n \n \n \"Bandelet 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\n\n
\n
@Article{le05:_bandel_image_approx_compr,\n  author =\t {Le Pennec, E. and Mallat, S.},\n  title =\t {Bandelet Image Approximation and Compression},\n  journal =\t {Multiscale Model. Sim.},\n  fjournal =\t {Multiscale Modeling and Simulation},\n  year =\t 2005,\n  volume =\t 4,\n  number =\t 3,\n  pages =\t {992--1039},\n  x-editorial-board ={yes},\n  x-international-audience ={yes},\n  keywords =\t {Article, Bandlets, TOP10, ThemeBandlet,\n                  ThemeBandlet},\n  pubtype =\t {Article},\n  subject =\t {Bandlets},\n  preprint =\t {Bandlets/2005-MMS-LPM.pdf},\n  reprint =\t {Bandlets/2005-MMS-LPM.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/Bandlets/2005-MMS-LPM.pdf},\n  reprintok =\t 1,\n  lang =\t {English},\n  doi =\t\t {10.1137/040619454}\n}\n\n%%% 2004\n\n\n%%% 2003\n\n
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\n  \n 2003\n \n \n (3)\n \n \n
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\n  \n Actes de conférence nationale\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n \n Bandelettes et représentation géométrique des images.\n \n \n \n \n\n\n \n Le Pennec, E.; and Mallat, S.\n\n\n \n\n\n\n In GRETSI 03, Paris, 2003. \n \n\n\n\n
\n\n\n\n \n \n \"Bandelettes 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{le03:_bandel,\n  author =\t {Le Pennec, E. and Mallat, S.},\n  title =\t {Bandelettes et représentation géométrique des\n                  images},\n  booktitle =\t {GRETSI 03},\n  year =\t 2003,\n  address =\t {Paris},\n  x-international-audience ={no},\n  x-proceedings ={yes},\n  x-invited-conference ={no},\n  keywords =\t {Actes, Bandlets, ThemeBandlet},\n  pubtype =\t {Actes de conférence nationale},\n  subject =\t {Bandlets},\n  pdf =\n                  {http://www.math.jussieu.fr/~lepennec/papers/gretsi03.pdf},\n  preprint =\t {Bandlets/2003-GRETSI-LPM.pdf},\n  reprint =\t {Bandlets/2003-GRETSI-LPM.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/Bandlets/2003-GRETSI-LPM.pdf},\n  reprintok =\t 1,\n  lang =\t {Francais}\n}\n\n
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\n  \n Proceedings of international conference\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n \n Geometrical Image Compression with Bandelets.\n \n \n \n \n\n\n \n Le Pennec, E.; and Mallat, S.\n\n\n \n\n\n\n In VCIP 03, Lugano, 2003. \n Special Session\n\n\n\n
\n\n\n\n \n \n \"Geometrical 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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@InProceedings{le03:_geomet_image_compr_bandel,\n  author =\t {Le Pennec, E. and Mallat, S.},\n  title =\t {Geometrical Image Compression with Bandelets},\n  booktitle =\t {VCIP 03},\n  year =\t 2003,\n  note =\t {Special Session},\n  address =\t {Lugano},\n  x-international-audience ={yes},\n  x-proceedings ={yes},\n  x-invited-conference ={yes},\n  keywords =\t {Proceedings, Bandlets, ThemeBandlet},\n  pubtype =\t {Proceedings of international conference},\n  subject =\t {Bandlets},\n  preprint =\t {Bandlets/2003-VCIP-LPM.pdf},\n  reprint =\t {Bandlets/2003-VCIP-LPM.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/Bandlets/2003-VCIP-LPM.pdf},\n  reprintok =\t 1,\n  lang =\t {English},\n  doi =\t\t {10.1117/12.509904}\n}\n\n
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\n  \n Technical report\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n \n Adaptation of regular grid filterings to irregular grids.\n \n \n \n \n\n\n \n Bernard, C.; and Le Pennec, E.\n\n\n \n\n\n\n Technical Report CMAP, 2003.\n \n\n\n\n
\n\n\n\n \n \n \"Adaptation 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
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@TechReport{bernard03:_adapt,\n  author =\t {Bernard, Ch. and Le Pennec, E.},\n  title =\t {Adaptation of regular grid filterings to irregular\n                  grids},\n  institution =\t {CMAP},\n  year =\t 2003,\n  keywords =\t {TechReport},\n  pubtype =\t {Technical report},\n  preprint =\t {Bandlets/2003-CMAP-BLP.pdf},\n  url_PDF = {http://lepennec.perso.math.cnrs.fr/Preprint/Bandlets/2003-CMAP-BLP.pdf},\n  lang =\t {English}\n}\n\n%%% 2002\n\n
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\n  \n Patent\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n \n Method and apparatus for processing or compressing n-dimensional signals with warped wavelets packets and bandelets.\n \n \n \n \n\n\n \n Bernard, C.; Kalifa, J.; Le Pennec, E.; and Mallat, S.\n\n\n \n\n\n\n 2002.\n \n\n\n\n
\n\n\n\n \n \n \"Method 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
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@Patent{bernard02:_method,\n  author =\t {Bernard, Ch. and Kalifa, J. and Le Pennec, E. and\n                  Mallat, S.},\n  title =\t {Method and apparatus for processing or compressing\n                  n-dimensional signals with warped wavelets packets\n                  and bandelets},\n  year =\t 2002,\n  number =\t {PCT/EP02/14903},\n  keywords =\t {Patent},\n  pubtype =\t {Patent},\n  reprint =\t {Patent/2006-BKLPM.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/Patent/2006-BKLPM.pdf},\n  reprintok =\t 1,\n  lang =\t {English}\n}\n\n%%% 2001\n\n
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\n  \n 2001\n \n \n (3)\n \n \n
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\n  \n Actes de conférence nationale\n \n \n (1)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n \n Représentation d'image par bandelettes et application à la compression.\n \n \n \n \n\n\n \n Le Pennec, E.; and Mallat, S.\n\n\n \n\n\n\n In GRETSI 01, Toulouse, 2001. \n \n\n\n\n
\n\n\n\n \n \n \"Représentation 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{le01:_repre,\n  author =\t {Le Pennec, E. and Mallat, S.},\n  title =\t {Représentation d'image par bandelettes et\n                  application à la compression},\n  booktitle =\t {GRETSI 01},\n  year =\t 2001,\n  address =\t {Toulouse},\n  x-international-audience ={no},\n  x-proceedings ={yes},\n  x-invited-conference ={no},\n  keywords =\t {Actes, Bandlets, ThemeBandlet},\n  pubtype =\t {Actes de conférence nationale},\n  subject =\t {Bandlets},\n  preprint =\t {Bandlets/2001-GRETSI-LPM.pdf},\n  reprint =\t {Bandlets/2001-GRETSI-LPM.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/Bandlets/2001-GRETSI-LPM.pdf},\n  reprintok =\t 1,\n  lang =\t {Francais}\n}\n\n%%% 2000\n\n
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\n  \n Patent\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n \n Method and apparatus for processing or compressing n-dimensional signals by foveal filtering along trajectories.\n \n \n \n \n\n\n \n Le Pennec, E.; and Mallat, S.\n\n\n \n\n\n\n 2001.\n \n\n\n\n
\n\n\n\n \n \n \"Method 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
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@Patent{le01:_method,\n  author =\t {Le Pennec, E. and Mallat, S.},\n  title =\t {Method and apparatus for processing or compressing\n                  n-dimensional signals by foveal filtering along\n                  trajectories},\n  year =\t 2001,\n  number =\t {09/834,587},\n  keywords =\t {Patent,TOP10},\n  pubtype =\t {Patent},\n  reprint =\t {Patent/2004-LPM.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/Patent/2004-LPM.pdf},\n  reprintok =\t 1,\n  lang =\t {English}\n}\n\n
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\n  \n Proceedings of international conference\n \n \n (1)\n \n \n
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\n \n \n
\n \n\n \n \n \n \n \n \n Bandelet Representations for Image Compression.\n \n \n \n \n\n\n \n Le Pennec, E.; and Mallat, S.\n\n\n \n\n\n\n In ICIP 01, Thessaloniki, 2001. \n Special Session\n\n\n\n
\n\n\n\n \n \n \"Bandelet 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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@InProceedings{le01:_bandel_repres_image_compr,\n  author =\t {Le Pennec, E. and Mallat, S.},\n  title =\t {Bandelet Representations for Image Compression},\n  booktitle =\t {ICIP 01},\n  year =\t 2001,\n  address =\t {Thessaloniki},\n  note =\t {Special Session},\n  x-international-audience ={yes},\n  x-proceedings ={yes},\n  x-invited-conference ={yes},\n  keywords =\t {Proceedings, Bandlets, ThemeBandlet},\n  pubtype =\t {Proceedings of international conference},\n  subject =\t {Bandlets},\n  preprint =\t {Bandlets/2001-ICIP-LPM.pdf},\n  reprint =\t {Bandlets/2001-ICIP-LPM.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/Bandlets/2001-ICIP-LPM.pdf},\n  reprintok =\t 1,\n  lang =\t {English},\n  doi =\t\t {10.1109/ICIP.2001.958939}\n}\n\n
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\n  \n 2000\n \n \n (1)\n \n \n
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\n  \n Proceedings of international conference\n \n \n (1)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n \n Image Compression with Geometrical Wavelets.\n \n \n \n \n\n\n \n Le Pennec, E.; and Mallat, S.\n\n\n \n\n\n\n In ICIP 00, Vancouver, 2000. \n \n\n\n\n
\n\n\n\n \n \n \"Image 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 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{le00:_image_compr_geomet_wavel,\n  author =\t {Le Pennec, E. and Mallat, S.},\n  title =\t {Image Compression with Geometrical Wavelets},\n  booktitle =\t {ICIP 00},\n  year =\t 2000,\n  address =\t {Vancouver},\n  x-international-audience ={yes},\n  x-proceedings ={yes},\n  x-invited-conference ={no},\n  keywords =\t {Proceedings, Bandlets, ThemeBandlet},\n  pubtype =\t {Proceedings of international conference},\n  subject =\t {Bandlets},\n  preprint =\t {Bandlets/2000-ICIP-LPM.pdf},\n  reprint =\t {Bandlets/2000-ICIP-LPM.pdf},\n  url_PDF =\n                  {http://lepennec.perso.math.cnrs.fr/Reprint/Bandlets/2000-ICIP-LPM.pdf},\n  reprintok =\t 1,\n  lang =\t {English},\n  doi =\t\t {10.1109/ICIP.2000.901045},\n}\n\n%%% 1999\n\n%%% 1998\n
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