

{"id":63,"date":"2018-12-07T19:34:11","date_gmt":"2018-12-07T18:34:11","guid":{"rendered":"https:\/\/project.inria.fr\/dirtydata\/?page_id=63"},"modified":"2019-03-26T13:26:57","modified_gmt":"2019-03-26T12:26:57","slug":"publications","status":"publish","type":"page","link":"https:\/\/project.inria.fr\/dirtydata\/publications\/","title":{"rendered":"Publications"},"content":{"rendered":"<p>   <!DOCTYPE html PUBLIC \"-\/\/W3C\/\/DTD XHTML 1.0 Transitional\/\/EN\" \"http:\/\/www.w3.org\/TR\/xhtml1\/DTD\/xhtml1-transitional.dtd\"> <html xmlns='http:\/\/www.w3.org\/1999\/xhtml' xml:lang='fr' lang='fr'> <head> <meta name=\"robots\" content=\"noindex, nofollow\" \/> <meta http-equiv=\"content-type\" content= \"text\/html;charset=UTF-8\" \/> <meta http-equiv=\"Content-Language\" content=\"fr\" \/> <link rel=\"stylesheet\" type=\"text\/css\" href=\"..\/css\/VisuGen.css\" \/> <link rel=\"stylesheet\" type=\"text\/css\" href=\"https:\/\/haltools.inria.fr\/\/css\/styles_publicationsHAL.css\" \/> <!-- Piwik haltools.inria.fr--> <script type=\"text\/javascript\">   var _paq = _paq || [];   _paq.push(['trackPageView']);   _paq.push(['enableLinkTracking']);   (function() {     var u=\"\/\/piwik.inria.fr\/\";     _paq.push(['setTrackerUrl', u+'piwik.php']);     _paq.push(['setSiteId', 25]);     var d=document, g=d.createElement('script'), s=d.getElementsByTagName('script')[0];     g.type='text\/javascript'; g.async=true; g.defer=true; g.src=u+'piwik.js'; s.parentNode.insertBefore(g,s);   })(); <\/script> <noscript><\/p>\n<p><img decoding=\"async\" src=\"\/\/piwik.inria.fr\/piwik.php?idsite=25\" style=\"border:0;\" alt=\"\" \/><\/p>\n<p><\/noscript> <!-- End Piwik Code -->  <title>Publications HAL du projet ANR.  ANR-17-CE23-0018<\/title> <\/head> <body> <\/p>\n<div id=\"res_script\">\n<p class='Rubrique'>2024<\/p>\n<p class='SousRubrique'>Journal articles<\/p>\n<dl class='NoticeResAvecVignette'>\n<dd class='Vignette'> <a href=\"https:\/\/hal.science\/hal-02024202v6\" target=\"_blank\"> <img decoding=\"async\" class=\"VignetteImg\" border=\"0\" src=\"https:\/\/thumb.ccsd.cnrs.fr\/9412535\/thumb\/little\" alt=\"\" \/><\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">titre<\/dt>\n<dd class=\"ValeurResAvecVignette Titre\"><a href=\"https:\/\/hal.science\/hal-02024202v6\" target=\"_blank\" >On the consistency of supervised learning with missing values<\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">auteur<\/dt>\n<dd class=\"ValeurResAvecVignette Auteurs\">Julie Josse, Jacob M. Chen, Nicolas Prost, Ga\u00ebl Varoquaux, Erwan Scornet<\/dd>\n<dt class=\"ChampResAvecVignette\">article<\/dt>\n<dd class=\"ValeurResAvecVignette article\"><i>Statistical Papers<\/i>, 2024, 65 (9), pp.5447-5479. <a target=\"_blank\" href=\"https:\/\/dx.doi.org\/10.1007\/s00362-024-01550-4\">&#x27E8;10.1007\/s00362-024-01550-4&#x27E9;<\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">Resume_court<\/dt>\n<dd class=\"ValeurResAvecVignette Debut_du_resume\">In many application settings, the data have missing entries which make analysis challenging. An abun &#8230;..<\/dd>\n<dt class=\"ChampResAvecVignette\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurResAvecVignette Fichier_joint\"> <a href=\"https:\/\/hal.science\/hal-02024202\/file\/main.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/hal.science\/hal-02024202\/file\/main.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/hal.science\/hal-02024202\/file\/main.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/hal.science\/hal-02024202v6\/bibtex\" target=\"_self\"> <img decoding=\"async\" alt=\"BibTex\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_bibtex3.png\" border=\"0\"  title=\"BibTex\" \/><\/a> <\/span><\/dd>\n<\/dl>\n<dl class='NoticeResAvecVignette'>\n<dd class='Vignette'> <a href=\"https:\/\/hal.science\/hal-03008276v2\" target=\"_blank\"> <img decoding=\"async\" class=\"VignetteImg\" border=\"0\" src=\"https:\/\/thumb.ccsd.cnrs.fr\/9147257\/thumb\/little\" alt=\"\" \/><\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">titre<\/dt>\n<dd class=\"ValeurResAvecVignette Titre\"><a href=\"https:\/\/hal.science\/hal-03008276v2\" target=\"_blank\" >Causal inference methods for combining randomized trials and observational studies: a review<\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">auteur<\/dt>\n<dd class=\"ValeurResAvecVignette Auteurs\">B\u00e9n\u00e9dicte Colnet, Imke Mayer, Guanhua Chen, Awa Dieng, Ruohong Li, Ga\u00ebl Varoquaux, Jean-Philippe Vert, Julie Josse, Shu Yang<\/dd>\n<dt class=\"ChampResAvecVignette\">article<\/dt>\n<dd class=\"ValeurResAvecVignette article\"><i>Statistical Science<\/i>, In press<\/dd>\n<dt class=\"ChampResAvecVignette\">Resume_court<\/dt>\n<dd class=\"ValeurResAvecVignette Debut_du_resume\">With increasing data availability, causal effects can be evaluated across different data sets, both  &#8230;..<\/dd>\n<dt class=\"ChampResAvecVignette\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurResAvecVignette Fichier_joint\"> <a href=\"https:\/\/hal.science\/hal-03008276\/file\/main.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/hal.science\/hal-03008276\/file\/main.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/hal.science\/hal-03008276\/file\/main.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/hal.science\/hal-03008276v2\/bibtex\" target=\"_self\"> <img decoding=\"async\" alt=\"BibTex\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_bibtex3.png\" border=\"0\"  title=\"BibTex\" \/><\/a> <\/span><\/dd>\n<\/dl>\n<p class='Rubrique'>2023<\/p>\n<p class='SousRubrique'>Journal articles<\/p>\n<dl class='NoticeResAvecVignette'>\n<dd class='Vignette'> <a href=\"https:\/\/hal.science\/hal-03848124v1\" target=\"_blank\"> <img decoding=\"async\" class=\"VignetteImg\" border=\"0\" src=\"https:\/\/thumb.ccsd.cnrs.fr\/9111881\/thumb\/little\" alt=\"\" \/><\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">titre<\/dt>\n<dd class=\"ValeurResAvecVignette Titre\"><a href=\"https:\/\/hal.science\/hal-03848124v1\" target=\"_blank\" >Relational Data Embeddings for Feature Enrichment with Background Information<\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">auteur<\/dt>\n<dd class=\"ValeurResAvecVignette Auteurs\">Alexis Cvetkov-Iliev, Alexandre Allauzen, Ga\u00ebl Varoquaux<\/dd>\n<dt class=\"ChampResAvecVignette\">article<\/dt>\n<dd class=\"ValeurResAvecVignette article\"><i>Machine Learning<\/i>, 2023, 112 (2), pp.687-720. <a target=\"_blank\" href=\"https:\/\/dx.doi.org\/10.1007\/s10994-022-06277-7\">&#x27E8;10.1007\/s10994-022-06277-7&#x27E9;<\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">Resume_court<\/dt>\n<dd class=\"ValeurResAvecVignette Debut_du_resume\">For many machine-learning tasks, augmenting the data table at hand with features built from external &#8230;..<\/dd>\n<dt class=\"ChampResAvecVignette\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurResAvecVignette Fichier_joint\"> <a href=\"https:\/\/hal.science\/hal-03848124\/file\/main.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/hal.science\/hal-03848124\/file\/main.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/hal.science\/hal-03848124\/file\/main.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/hal.science\/hal-03848124v1\/bibtex\" target=\"_self\"> <img decoding=\"async\" alt=\"BibTex\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_bibtex3.png\" border=\"0\"  title=\"BibTex\" \/><\/a> <\/span><\/dd>\n<\/dl>\n<p class='SousRubrique'>Book sections<\/p>\n<dl class='NoticeResAvecVignette'>\n<dd class='Vignette'> <a href=\"https:\/\/hal.science\/hal-03682454v6\" target=\"_blank\"> <img decoding=\"async\" class=\"VignetteImg\" border=\"0\" src=\"https:\/\/thumb.ccsd.cnrs.fr\/9831840\/thumb\/little\" alt=\"\" \/><\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">titre<\/dt>\n<dd class=\"ValeurResAvecVignette Titre\"><a href=\"https:\/\/hal.science\/hal-03682454v6\" target=\"_blank\" >Evaluating machine learning models and their diagnostic value<\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">auteur<\/dt>\n<dd class=\"ValeurResAvecVignette Auteurs\">Ga\u00ebl Varoquaux, Olivier Colliot<\/dd>\n<dt class=\"ChampResAvecVignette\">article<\/dt>\n<dd class=\"ValeurResAvecVignette article\">Olivier Colliot. <i>Machine Learning for Brain Disorders<\/i>, Springer, 2023<\/dd>\n<dt class=\"ChampResAvecVignette\">Resume_court<\/dt>\n<dd class=\"ValeurResAvecVignette Debut_du_resume\">This chapter describes model validation, a crucial part of machine learning whether it is to select  &#8230;..<\/dd>\n<dt class=\"ChampResAvecVignette\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurResAvecVignette Fichier_joint\"> <a href=\"https:\/\/hal.science\/hal-03682454\/file\/Chapter%2020%20-%20Final%20-%20Corrected.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/hal.science\/hal-03682454\/file\/Chapter%2020%20-%20Final%20-%20Corrected.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/hal.science\/hal-03682454\/file\/Chapter%2020%20-%20Final%20-%20Corrected.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/hal.science\/hal-03682454v6\/bibtex\" target=\"_self\"> <img decoding=\"async\" alt=\"BibTex\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_bibtex3.png\" border=\"0\"  title=\"BibTex\" \/><\/a> <\/span><\/dd>\n<\/dl>\n<p class='Rubrique'>2022<\/p>\n<p class='SousRubrique'>Journal articles<\/p>\n<dl class='NoticeRes'>\n<dt class=\"ChampResAvecVignette\">titre<\/dt>\n<dd class=\"ValeurResAvecVignette Titre\"><a href=\"https:\/\/hal.science\/hal-03818456v1\" target=\"_blank\" >Machine learning for medical imaging: methodological failures and recommendations for the future<\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">auteur<\/dt>\n<dd class=\"ValeurResAvecVignette Auteurs\">Ga\u00ebl Varoquaux, Veronika Cheplygina<\/dd>\n<dt class=\"ChampResAvecVignette\">article<\/dt>\n<dd class=\"ValeurResAvecVignette article\"><i>npj Digital Medicine<\/i>, 2022, 5 (1), pp.48. <a target=\"_blank\" href=\"https:\/\/dx.doi.org\/10.1038\/s41746-022-00592-y\">&#x27E8;10.1038\/s41746-022-00592-y&#x27E9;<\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">Resume_court<\/dt>\n<dd class=\"ValeurResAvecVignette Debut_du_resume\">Research in computer analysis of medical images bears many promises to improve patients\u2019 health. H &#8230;..<\/dd>\n<dt class=\"ChampResAvecVignette\">Acc\u00e8s au bibtex<\/dt>\n<dd class=\"ValeurResAvecVignette LienBibtex\"> <a href=\"https:\/\/arxiv.org\/pdf\/2103.10292\"  target=\"_blank\"><img decoding=\"async\" alt=\"https:\/\/arxiv.org\/pdf\/2103.10292\" src=\"https:\/\/haltools.inria.fr\/images\/arxiv.gif\" border=\"0\" title=\"arXiv PDF\" width=\"16px\" height=\"16px\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/hal.science\/hal-03818456v1\/bibtex\" target=\"_self\"> <img decoding=\"async\" alt=\"BibTex\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_bibtex3.png\" border=\"0\"  title=\"BibTex\" \/><\/a> <\/span><\/dd>\n<\/dl>\n<dl class='NoticeResAvecVignette'>\n<dd class='Vignette'> <a href=\"https:\/\/hal.science\/hal-03473691v3\" target=\"_blank\"> <img decoding=\"async\" class=\"VignetteImg\" border=\"0\" src=\"https:\/\/thumb.ccsd.cnrs.fr\/9189532\/thumb\/little\" alt=\"\" \/><\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">titre<\/dt>\n<dd class=\"ValeurResAvecVignette Titre\"><a href=\"https:\/\/hal.science\/hal-03473691v3\" target=\"_blank\" >Causal effect on a target population: a sensitivity analysis to handle missing covariates<\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">auteur<\/dt>\n<dd class=\"ValeurResAvecVignette Auteurs\">B\u00e9n\u00e9dicte Colnet, Julie Josse, Ga\u00ebl Varoquaux, Erwan Scornet<\/dd>\n<dt class=\"ChampResAvecVignette\">article<\/dt>\n<dd class=\"ValeurResAvecVignette article\"><i>Journal of Causal Inference<\/i>, 2022, 10 (1), pp.372-414. <a target=\"_blank\" href=\"https:\/\/dx.doi.org\/10.1515\/jci-2021-0059\">&#x27E8;10.1515\/jci-2021-0059&#x27E9;<\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">Resume_court<\/dt>\n<dd class=\"ValeurResAvecVignette Debut_du_resume\">Randomized Controlled Trials (RCTs) are often considered as the gold standard to conclude on the cau &#8230;..<\/dd>\n<dt class=\"ChampResAvecVignette\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurResAvecVignette Fichier_joint\"> <a href=\"https:\/\/hal.science\/hal-03473691\/file\/JCI-version-finale.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/hal.science\/hal-03473691\/file\/JCI-version-finale.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/hal.science\/hal-03473691\/file\/JCI-version-finale.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/hal.science\/hal-03473691v3\/bibtex\" target=\"_self\"> <img decoding=\"async\" alt=\"BibTex\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_bibtex3.png\" border=\"0\"  title=\"BibTex\" \/><\/a> <\/span><\/dd>\n<\/dl>\n<dl class='NoticeResAvecVignette'>\n<dd class='Vignette'> <a href=\"https:\/\/inria.hal.science\/hal-03607651v1\" target=\"_blank\"> <img decoding=\"async\" class=\"VignetteImg\" border=\"0\" src=\"https:\/\/thumb.ccsd.cnrs.fr\/8995390\/thumb\/little\" alt=\"\" \/><\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">titre<\/dt>\n<dd class=\"ValeurResAvecVignette Titre\"><a href=\"https:\/\/inria.hal.science\/hal-03607651v1\" target=\"_blank\" >How to remove or control confounds in predictive models, with applications to brain biomarkers<\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">auteur<\/dt>\n<dd class=\"ValeurResAvecVignette Auteurs\">Darya Chyzhyk, Ga\u00ebl Varoquaux, Michael Milham, Bertrand Thirion<\/dd>\n<dt class=\"ChampResAvecVignette\">article<\/dt>\n<dd class=\"ValeurResAvecVignette article\"><i>GigaScience<\/i>, 2022, 11, <a target=\"_blank\" href=\"https:\/\/dx.doi.org\/10.1093\/gigascience\/giac014\">&#x27E8;10.1093\/gigascience\/giac014&#x27E9;<\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">Resume_court<\/dt>\n<dd class=\"ValeurResAvecVignette Debut_du_resume\">Background : With increasing data sizes and more easily available computational methods, neuroscienc &#8230;..<\/dd>\n<dt class=\"ChampResAvecVignette\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurResAvecVignette Fichier_joint\"> <a href=\"https:\/\/inria.hal.science\/hal-03607651\/file\/giac014.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/inria.hal.science\/hal-03607651\/file\/giac014.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/inria.hal.science\/hal-03607651\/file\/giac014.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/inria.hal.science\/hal-03607651v1\/bibtex\" target=\"_self\"> <img decoding=\"async\" alt=\"BibTex\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_bibtex3.png\" border=\"0\"  title=\"BibTex\" \/><\/a> <\/span><\/dd>\n<\/dl>\n<dl class='NoticeResAvecVignette'>\n<dd class='Vignette'> <a href=\"https:\/\/hal.science\/hal-03647434v2\" target=\"_blank\"> <img decoding=\"async\" class=\"VignetteImg\" border=\"0\" src=\"https:\/\/thumb.ccsd.cnrs.fr\/9020093\/thumb\/little\" alt=\"\" \/><\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">titre<\/dt>\n<dd class=\"ValeurResAvecVignette Titre\"><a href=\"https:\/\/hal.science\/hal-03647434v2\" target=\"_blank\" >Analytics on Non-Normalized Data Sources: more Learning, rather than more Cleaning<\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">auteur<\/dt>\n<dd class=\"ValeurResAvecVignette Auteurs\">Alexis Cvetkov-Iliev, Alexandre Allauzen, Ga\u00ebl Varoquaux<\/dd>\n<dt class=\"ChampResAvecVignette\">article<\/dt>\n<dd class=\"ValeurResAvecVignette article\"><i>IEEE Access<\/i>, In press, 10, pp.42420-42431. <a target=\"_blank\" href=\"https:\/\/dx.doi.org\/10.1109\/ACCESS.2022.3168013\">&#x27E8;10.1109\/ACCESS.2022.3168013&#x27E9;<\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">Resume_court<\/dt>\n<dd class=\"ValeurResAvecVignette Debut_du_resume\">Data analysis is increasingly performed over data assembled from uncontrolled sources, facing incons &#8230;..<\/dd>\n<dt class=\"ChampResAvecVignette\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurResAvecVignette Fichier_joint\"> <a href=\"https:\/\/hal.science\/hal-03647434\/file\/final.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/hal.science\/hal-03647434\/file\/final.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/hal.science\/hal-03647434\/file\/final.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/hal.science\/hal-03647434v2\/bibtex\" target=\"_self\"> <img decoding=\"async\" alt=\"BibTex\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_bibtex3.png\" border=\"0\"  title=\"BibTex\" \/><\/a> <\/span><\/dd>\n<\/dl>\n<dl class='NoticeResAvecVignette'>\n<dd class='Vignette'> <a href=\"https:\/\/hal.science\/hal-03526292v2\" target=\"_blank\"> <img decoding=\"async\" class=\"VignetteImg\" border=\"0\" src=\"https:\/\/thumb.ccsd.cnrs.fr\/8980782\/thumb\/little\" alt=\"\" \/><\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">titre<\/dt>\n<dd class=\"ValeurResAvecVignette Titre\"><a href=\"https:\/\/hal.science\/hal-03526292v2\" target=\"_blank\" >Benchmarking missing-values approaches for predictive models on health databases<\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">auteur<\/dt>\n<dd class=\"ValeurResAvecVignette Auteurs\">Alexandre Perez-Lebel, Ga\u00ebl Varoquaux, Marine Le Morvan, Julie Josse, Jean-Baptiste Poline<\/dd>\n<dt class=\"ChampResAvecVignette\">article<\/dt>\n<dd class=\"ValeurResAvecVignette article\"><i>GigaScience<\/i>, In press, <a target=\"_blank\" href=\"https:\/\/dx.doi.org\/10.1093\/gigascience\/giac013\">&#x27E8;10.1093\/gigascience\/giac013&#x27E9;<\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">Resume_court<\/dt>\n<dd class=\"ValeurResAvecVignette Debut_du_resume\">BACKGROUND: As databases grow larger, it becomes harder to fully control their collection, and they  &#8230;..<\/dd>\n<dt class=\"ChampResAvecVignette\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurResAvecVignette Fichier_joint\"> <a href=\"https:\/\/hal.science\/hal-03526292\/file\/Benchmarking%20missing-values%20approaches%20for%20predictive%20models%20on%20health%20databases.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/hal.science\/hal-03526292\/file\/Benchmarking%20missing-values%20approaches%20for%20predictive%20models%20on%20health%20databases.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/hal.science\/hal-03526292\/file\/Benchmarking%20missing-values%20approaches%20for%20predictive%20models%20on%20health%20databases.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/hal.science\/hal-03526292v2\/bibtex\" target=\"_self\"> <img decoding=\"async\" alt=\"BibTex\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_bibtex3.png\" border=\"0\"  title=\"BibTex\" \/><\/a> <\/span><\/dd>\n<\/dl>\n<p class='Rubrique'>2021<\/p>\n<p class='SousRubrique'>Journal articles<\/p>\n<dl class='NoticeResAvecVignette'>\n<dd class='Vignette'> <a href=\"https:\/\/hal.science\/hal-03293375v1\" target=\"_blank\"> <img decoding=\"async\" class=\"VignetteImg\" border=\"0\" src=\"https:\/\/thumb.ccsd.cnrs.fr\/8854201\/thumb\/little\" alt=\"\" \/><\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">titre<\/dt>\n<dd class=\"ValeurResAvecVignette Titre\"><a href=\"https:\/\/hal.science\/hal-03293375v1\" target=\"_blank\" >Preventing dataset shift from breaking machine-learning biomarkers<\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">auteur<\/dt>\n<dd class=\"ValeurResAvecVignette Auteurs\">J\u00e9r\u00f4me Dock\u00e8s, Ga\u00ebl Varoquaux, Jean-Baptiste Poline<\/dd>\n<dt class=\"ChampResAvecVignette\">article<\/dt>\n<dd class=\"ValeurResAvecVignette article\"><i>GigaScience<\/i>, In press, <a target=\"_blank\" href=\"https:\/\/dx.doi.org\/10.1093\/gigascience\/giab055\">&#x27E8;10.1093\/gigascience\/giab055&#x27E9;<\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">Resume_court<\/dt>\n<dd class=\"ValeurResAvecVignette Debut_du_resume\">Machine learning brings the hope of finding new biomarkers extracted from cohorts with rich biomedic &#8230;..<\/dd>\n<dt class=\"ChampResAvecVignette\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurResAvecVignette Fichier_joint\"> <a href=\"https:\/\/hal.science\/hal-03293375\/file\/main.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/hal.science\/hal-03293375\/file\/main.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/hal.science\/hal-03293375\/file\/main.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/hal.science\/hal-03293375v1\/bibtex\" target=\"_self\"> <img decoding=\"async\" alt=\"BibTex\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_bibtex3.png\" border=\"0\"  title=\"BibTex\" \/><\/a> <\/span><\/dd>\n<\/dl>\n<p class='SousRubrique'>Conference papers<\/p>\n<dl class='NoticeResAvecVignette'>\n<dd class='Vignette'> <a href=\"https:\/\/hal.science\/hal-03474791v2\" target=\"_blank\"> <img decoding=\"async\" class=\"VignetteImg\" border=\"0\" src=\"https:\/\/thumb.ccsd.cnrs.fr\/8934911\/thumb\/little\" alt=\"\" \/><\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">titre<\/dt>\n<dd class=\"ValeurResAvecVignette Titre\"><a href=\"https:\/\/hal.science\/hal-03474791v2\" target=\"_blank\" >AI as statistical methods for imperfect theories<\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">auteur<\/dt>\n<dd class=\"ValeurResAvecVignette Auteurs\">Ga\u00ebl Varoquaux<\/dd>\n<dt class=\"ChampResAvecVignette\">article<\/dt>\n<dd class=\"ValeurResAvecVignette article\"><i>NeurIPS 2021 &#8211; 35th Conference on Neural Information Processing Systems. Workshop: AI for Science<\/i>, Dec 2021, Virtual, France<\/dd>\n<dt class=\"ChampResAvecVignette\">Resume_court<\/dt>\n<dd class=\"ValeurResAvecVignette Debut_du_resume\">Science has progressed by reasoning on what models could not predict because they were missing impor &#8230;..<\/dd>\n<dt class=\"ChampResAvecVignette\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurResAvecVignette Fichier_joint\"> <a href=\"https:\/\/hal.science\/hal-03474791\/file\/paper.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/hal.science\/hal-03474791\/file\/paper.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/hal.science\/hal-03474791\/file\/paper.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/hal.science\/hal-03474791v2\/bibtex\" target=\"_self\"> <img decoding=\"async\" alt=\"BibTex\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_bibtex3.png\" border=\"0\"  title=\"BibTex\" \/><\/a> <\/span><\/dd>\n<\/dl>\n<dl class='NoticeResAvecVignette'>\n<dd class='Vignette'> <a href=\"https:\/\/hal.science\/hal-03243931v2\" target=\"_blank\"> <img decoding=\"async\" class=\"VignetteImg\" border=\"0\" src=\"https:\/\/thumb.ccsd.cnrs.fr\/8924949\/thumb\/little\" alt=\"\" \/><\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">titre<\/dt>\n<dd class=\"ValeurResAvecVignette Titre\"><a href=\"https:\/\/hal.science\/hal-03243931v2\" target=\"_blank\" >What&#8217;s a good imputation to predict with missing values?<\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">auteur<\/dt>\n<dd class=\"ValeurResAvecVignette Auteurs\">Marine Le Morvan, Julie Josse, Erwan Scornet, Ga\u00ebl Varoquaux<\/dd>\n<dt class=\"ChampResAvecVignette\">article<\/dt>\n<dd class=\"ValeurResAvecVignette article\"><i>NeurIPS 2021 &#8211; 35th Conference on Neural Information Processing Systems<\/i>, Dec 2021, Virtual, France. <a target=\"_blank\" href=\"https:\/\/dx.doi.org\/10.48550\/arXiv.2106.00311\">&#x27E8;10.48550\/arXiv.2106.00311&#x27E9;<\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">Resume_court<\/dt>\n<dd class=\"ValeurResAvecVignette Debut_du_resume\">How to learn a good predictor on data with missing values? Most efforts focus on first imputing as w &#8230;..<\/dd>\n<dt class=\"ChampResAvecVignette\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurResAvecVignette Fichier_joint\"> <a href=\"https:\/\/hal.science\/hal-03243931\/file\/LeMorvan2021_ImputeThenRegress.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/hal.science\/hal-03243931\/file\/LeMorvan2021_ImputeThenRegress.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/hal.science\/hal-03243931\/file\/LeMorvan2021_ImputeThenRegress.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/hal.science\/hal-03243931v2\/bibtex\" target=\"_self\"> <img decoding=\"async\" alt=\"BibTex\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_bibtex3.png\" border=\"0\"  title=\"BibTex\" \/><\/a> <\/span><\/dd>\n<\/dl>\n<dl class='NoticeResAvecVignette'>\n<dd class='Vignette'> <a href=\"https:\/\/hal.science\/hal-03177159v1\" target=\"_blank\"> <img decoding=\"async\" class=\"VignetteImg\" border=\"0\" src=\"https:\/\/thumb.ccsd.cnrs.fr\/8797511\/thumb\/little\" alt=\"\" \/><\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">titre<\/dt>\n<dd class=\"ValeurResAvecVignette Titre\"><a href=\"https:\/\/hal.science\/hal-03177159v1\" target=\"_blank\" >Accounting for variance in machine learning benchmarks<\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">auteur<\/dt>\n<dd class=\"ValeurResAvecVignette Auteurs\">Xavier Bouthillier, Pierre Delaunay, Mirko Bronzi, Assya Trofimov, Brennan Nichyporuk, Justin Szeto, Naz Sepah, Edward Raff, Kanika Madan, Vikram Voleti, Samira Ebrahimi Kahou, Vincent Michalski, Dmitriy Serdyuk, Tal Arbel, Chris Pal, Ga\u00ebl Varoquaux, Pascal Vincent<\/dd>\n<dt class=\"ChampResAvecVignette\">article<\/dt>\n<dd class=\"ValeurResAvecVignette article\"><i>MLsys 2021 &#8211; 4th Conference on Machine Learning and Systems<\/i>, Apr 2021, San Francisco (virtual), United States<\/dd>\n<dt class=\"ChampResAvecVignette\">Resume_court<\/dt>\n<dd class=\"ValeurResAvecVignette Debut_du_resume\">Strong empirical evidence that one machine-learning algorithm A outperforms another one B ideally ca &#8230;..<\/dd>\n<dt class=\"ChampResAvecVignette\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurResAvecVignette Fichier_joint\"> <a href=\"https:\/\/hal.science\/hal-03177159\/file\/main.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/hal.science\/hal-03177159\/file\/main.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/hal.science\/hal-03177159\/file\/main.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/hal.science\/hal-03177159v1\/bibtex\" target=\"_self\"> <img decoding=\"async\" alt=\"BibTex\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_bibtex3.png\" border=\"0\"  title=\"BibTex\" \/><\/a> <\/span><\/dd>\n<\/dl>\n<dl class='NoticeResAvecVignette'>\n<dd class='Vignette'> <a href=\"https:\/\/hal.science\/hal-03086044v2\" target=\"_blank\"> <img decoding=\"async\" class=\"VignetteImg\" border=\"0\" src=\"https:\/\/thumb.ccsd.cnrs.fr\/8824597\/thumb\/little\" alt=\"\" \/><\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">titre<\/dt>\n<dd class=\"ValeurResAvecVignette Titre\"><a href=\"https:\/\/hal.science\/hal-03086044v2\" target=\"_blank\" >A lightweight neural model for biomedical entity linking<\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">auteur<\/dt>\n<dd class=\"ValeurResAvecVignette Auteurs\">Lihu Chen, Ga\u00ebl Varoquaux, Fabian Suchanek<\/dd>\n<dt class=\"ChampResAvecVignette\">article<\/dt>\n<dd class=\"ValeurResAvecVignette article\"><i>AAAI 2021 &#8211; The Thirty-Fifth Conference on Artificial Intelligence<\/i>, Association for the Advancement of Artificial Intelligence, Feb 2021, Palo Alto (virtual), United States. pp.12657-12665<\/dd>\n<dt class=\"ChampResAvecVignette\">Resume_court<\/dt>\n<dd class=\"ValeurResAvecVignette Debut_du_resume\">Biomedical entity linking aims to map biomedical mentions, such as diseases and drugs, to standard e &#8230;..<\/dd>\n<dt class=\"ChampResAvecVignette\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurResAvecVignette Fichier_joint\"> <a href=\"https:\/\/hal.science\/hal-03086044\/file\/Biomedical_Entity_Linking.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/hal.science\/hal-03086044\/file\/Biomedical_Entity_Linking.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/hal.science\/hal-03086044\/file\/Biomedical_Entity_Linking.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/hal.science\/hal-03086044v2\/bibtex\" target=\"_self\"> <img decoding=\"async\" alt=\"BibTex\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_bibtex3.png\" border=\"0\"  title=\"BibTex\" \/><\/a> <\/span><\/dd>\n<\/dl>\n<p class='Rubrique'>2020<\/p>\n<p class='SousRubrique'>Journal articles<\/p>\n<dl class='NoticeResAvecVignette'>\n<dd class='Vignette'> <a href=\"https:\/\/hal.science\/hal-02329437v2\" target=\"_blank\"> <img decoding=\"async\" class=\"VignetteImg\" border=\"0\" src=\"https:\/\/thumb.ccsd.cnrs.fr\/8556863\/thumb\/little\" alt=\"\" \/><\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">titre<\/dt>\n<dd class=\"ValeurResAvecVignette Titre\"><a href=\"https:\/\/hal.science\/hal-02329437v2\" target=\"_blank\" >Tropical Cyclone Track Forecasting using Fused Deep Learning from Aligned Reanalysis Data<\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">auteur<\/dt>\n<dd class=\"ValeurResAvecVignette Auteurs\">Sophie Giffard-Roisin, Mo Yang, Guillaume Charpiat, Christina Kumler Bonfanti, Bal\u00e1zs K\u00e9gl, Claire Monteleoni<\/dd>\n<dt class=\"ChampResAvecVignette\">article<\/dt>\n<dd class=\"ValeurResAvecVignette article\"><i>Frontiers in Big Data<\/i>, 2020, 3, pp.1. <a target=\"_blank\" href=\"https:\/\/dx.doi.org\/10.3389\/fdata.2020.00001\">&#x27E8;10.3389\/fdata.2020.00001&#x27E9;<\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">Resume_court<\/dt>\n<dd class=\"ValeurResAvecVignette Debut_du_resume\">The forecast of tropical cyclone trajectories is crucial for the protection of people and property.  &#8230;..<\/dd>\n<dt class=\"ChampResAvecVignette\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurResAvecVignette Fichier_joint\"> <a href=\"https:\/\/hal.science\/hal-02329437\/file\/Frontiers_journal_author_version.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/hal.science\/hal-02329437\/file\/Frontiers_journal_author_version.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/hal.science\/hal-02329437\/file\/Frontiers_journal_author_version.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/hal.science\/hal-02329437v2\/bibtex\" target=\"_self\"> <img decoding=\"async\" alt=\"BibTex\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_bibtex3.png\" border=\"0\"  title=\"BibTex\" \/><\/a> <\/span><\/dd>\n<\/dl>\n<dl class='NoticeResAvecVignette'>\n<dd class='Vignette'> <a href=\"https:\/\/inria.hal.science\/hal-02171256v5\" target=\"_blank\"> <img decoding=\"async\" class=\"VignetteImg\" border=\"0\" src=\"https:\/\/thumb.ccsd.cnrs.fr\/8616436\/thumb\/little\" alt=\"\" \/><\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">titre<\/dt>\n<dd class=\"ValeurResAvecVignette Titre\"><a href=\"https:\/\/inria.hal.science\/hal-02171256v5\" target=\"_blank\" >Encoding high-cardinality string categorical variables<\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">auteur<\/dt>\n<dd class=\"ValeurResAvecVignette Auteurs\">Patricio Cerda, Ga\u00ebl Varoquaux<\/dd>\n<dt class=\"ChampResAvecVignette\">article<\/dt>\n<dd class=\"ValeurResAvecVignette article\"><i>IEEE Transactions on Knowledge and Data Engineering<\/i>, In press, <a target=\"_blank\" href=\"https:\/\/dx.doi.org\/10.1109\/TKDE.2020.2992529\">&#x27E8;10.1109\/TKDE.2020.2992529&#x27E9;<\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">Resume_court<\/dt>\n<dd class=\"ValeurResAvecVignette Debut_du_resume\">Statistical models usually require vector representations of categorical variables, using for instan &#8230;..<\/dd>\n<dt class=\"ChampResAvecVignette\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurResAvecVignette Fichier_joint\"> <a href=\"https:\/\/inria.hal.science\/hal-02171256\/file\/article.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/inria.hal.science\/hal-02171256\/file\/article.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/inria.hal.science\/hal-02171256\/file\/article.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/inria.hal.science\/hal-02171256v5\/bibtex\" target=\"_self\"> <img decoding=\"async\" alt=\"BibTex\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_bibtex3.png\" border=\"0\"  title=\"BibTex\" \/><\/a> <\/span><\/dd>\n<\/dl>\n<dl class='NoticeResAvecVignette'>\n<dd class='Vignette'> <a href=\"https:\/\/imt.hal.science\/hal-03108522v1\" target=\"_blank\"> <img decoding=\"async\" class=\"VignetteImg\" border=\"0\" src=\"https:\/\/thumb.ccsd.cnrs.fr\/8770604\/thumb\/little\" alt=\"\" \/><\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">titre<\/dt>\n<dd class=\"ValeurResAvecVignette Titre\"><a href=\"https:\/\/imt.hal.science\/hal-03108522v1\" target=\"_blank\" >An Experimental Study of State-of-the-Art Entity Alignment Approaches<\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">auteur<\/dt>\n<dd class=\"ValeurResAvecVignette Auteurs\">Xiang Zhao, Weixin Zeng, Jiuyang Tang, Wei Wang\u200b, Fabian Suchanek<\/dd>\n<dt class=\"ChampResAvecVignette\">article<\/dt>\n<dd class=\"ValeurResAvecVignette article\"><i>IEEE Transactions on Knowledge and Data Engineering<\/i>, 2020, <a target=\"_blank\" href=\"https:\/\/dx.doi.org\/10.1109\/TKDE.2020.3018741\">&#x27E8;10.1109\/TKDE.2020.3018741&#x27E9;<\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">Resume_court<\/dt>\n<dd class=\"ValeurResAvecVignette Debut_du_resume\">Entity alignment (EA) finds equivalent entities that are located in different knowledge graphs (KGs) &#8230;..<\/dd>\n<dt class=\"ChampResAvecVignette\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurResAvecVignette Fichier_joint\"> <a href=\"https:\/\/imt.hal.science\/hal-03108522\/file\/tkde-2020.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/imt.hal.science\/hal-03108522\/file\/tkde-2020.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/imt.hal.science\/hal-03108522\/file\/tkde-2020.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/imt.hal.science\/hal-03108522v1\/bibtex\" target=\"_self\"> <img decoding=\"async\" alt=\"BibTex\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_bibtex3.png\" border=\"0\"  title=\"BibTex\" \/><\/a> <\/span><\/dd>\n<\/dl>\n<p class='SousRubrique'>Conference papers<\/p>\n<dl class='NoticeResAvecVignette'>\n<dd class='Vignette'> <a href=\"https:\/\/hal.science\/hal-02888867v3\" target=\"_blank\"> <img decoding=\"async\" class=\"VignetteImg\" border=\"0\" src=\"https:\/\/thumb.ccsd.cnrs.fr\/8719822\/thumb\/little\" alt=\"\" \/><\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">titre<\/dt>\n<dd class=\"ValeurResAvecVignette Titre\"><a href=\"https:\/\/hal.science\/hal-02888867v3\" target=\"_blank\" >NeuMiss networks: differentiable programming for supervised learning with missing values<\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">auteur<\/dt>\n<dd class=\"ValeurResAvecVignette Auteurs\">Marine Le Morvan, Julie Josse, Thomas Moreau, Erwan Scornet, Ga\u00ebl Varoquaux<\/dd>\n<dt class=\"ChampResAvecVignette\">article<\/dt>\n<dd class=\"ValeurResAvecVignette article\"><i>NeurIPS 2020 &#8211; 34th Conference on Neural Information Processing Systems<\/i>, Dec 2020, Vancouver \/ Virtual, Canada<\/dd>\n<dt class=\"ChampResAvecVignette\">Resume_court<\/dt>\n<dd class=\"ValeurResAvecVignette Debut_du_resume\">The presence of missing values makes supervised learning much more challenging. Indeed, previous wor &#8230;..<\/dd>\n<dt class=\"ChampResAvecVignette\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurResAvecVignette Fichier_joint\"> <a href=\"https:\/\/hal.science\/hal-02888867\/file\/main.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/hal.science\/hal-02888867\/file\/main.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/hal.science\/hal-02888867\/file\/main.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/hal.science\/hal-02888867v3\/bibtex\" target=\"_self\"> <img decoding=\"async\" alt=\"BibTex\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_bibtex3.png\" border=\"0\"  title=\"BibTex\" \/><\/a> <\/span><\/dd>\n<\/dl>\n<dl class='NoticeResAvecVignette'>\n<dd class='Vignette'> <a href=\"https:\/\/hal.science\/hal-02464569v2\" target=\"_blank\"> <img decoding=\"async\" class=\"VignetteImg\" border=\"0\" src=\"https:\/\/thumb.ccsd.cnrs.fr\/8610633\/thumb\/little\" alt=\"\" \/><\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">titre<\/dt>\n<dd class=\"ValeurResAvecVignette Titre\"><a href=\"https:\/\/hal.science\/hal-02464569v2\" target=\"_blank\" >Linear predictor on linearly-generated data with missing values: non consistency and solutions<\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">auteur<\/dt>\n<dd class=\"ValeurResAvecVignette Auteurs\">Marine Le Morvan, Nicolas Prost, Julie Josse, Erwan Scornet, Ga\u00ebl Varoquaux<\/dd>\n<dt class=\"ChampResAvecVignette\">article<\/dt>\n<dd class=\"ValeurResAvecVignette article\"><i>AISTATS 2020 &#8211; International Conference on Artificial Intelligence and Statistics<\/i>, Aug 2020, Online, France. pp.3165-3174<\/dd>\n<dt class=\"ChampResAvecVignette\">Resume_court<\/dt>\n<dd class=\"ValeurResAvecVignette Debut_du_resume\">We consider building predictors when the data have missing values. We study the seemingly-simple cas &#8230;..<\/dd>\n<dt class=\"ChampResAvecVignette\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurResAvecVignette Fichier_joint\"> <a href=\"https:\/\/hal.science\/hal-02464569\/file\/aistats.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/hal.science\/hal-02464569\/file\/aistats.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/hal.science\/hal-02464569\/file\/aistats.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/hal.science\/hal-02464569v2\/bibtex\" target=\"_self\"> <img decoding=\"async\" alt=\"BibTex\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_bibtex3.png\" border=\"0\"  title=\"BibTex\" \/><\/a> <\/span><\/dd>\n<\/dl>\n<p class='Rubrique'>2019<\/p>\n<p class='SousRubrique'>Conference papers<\/p>\n<dl class='NoticeResAvecVignette'>\n<dd class='Vignette'> <a href=\"https:\/\/inria.hal.science\/hal-02292545v2\" target=\"_blank\"> <img decoding=\"async\" class=\"VignetteImg\" border=\"0\" src=\"https:\/\/thumb.ccsd.cnrs.fr\/8507047\/thumb\/little\" alt=\"\" \/><\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">titre<\/dt>\n<dd class=\"ValeurResAvecVignette Titre\"><a href=\"https:\/\/inria.hal.science\/hal-02292545v2\" target=\"_blank\" >Comparing distributions: $l1$ geometry improves kernel two-sample testing<\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">auteur<\/dt>\n<dd class=\"ValeurResAvecVignette Auteurs\">Meyer Scetbon, Ga\u00ebl Varoquaux<\/dd>\n<dt class=\"ChampResAvecVignette\">article<\/dt>\n<dd class=\"ValeurResAvecVignette article\"><i>NeurIPS 2019 &#8211; 33th Conference on Neural Information Processing Systems<\/i>, Dec 2019, Vancouver, Canada<\/dd>\n<dt class=\"ChampResAvecVignette\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurResAvecVignette Fichier_joint\"> <a href=\"https:\/\/inria.hal.science\/hal-02292545\/file\/NIPS_L1_test-HAL-v2%20%281%29.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/inria.hal.science\/hal-02292545\/file\/NIPS_L1_test-HAL-v2%20%281%29.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/inria.hal.science\/hal-02292545\/file\/NIPS_L1_test-HAL-v2%20%281%29.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/inria.hal.science\/hal-02292545v2\/bibtex\" target=\"_self\"> <img decoding=\"async\" alt=\"BibTex\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_bibtex3.png\" border=\"0\"  title=\"BibTex\" \/><\/a> <\/span><\/dd>\n<\/dl>\n<p class='Rubrique'>2018<\/p>\n<p class='SousRubrique'>Journal articles<\/p>\n<dl class='NoticeResAvecVignette'>\n<dd class='Vignette'> <a href=\"https:\/\/inserm.hal.science\/inserm-02146700v1\" target=\"_blank\"> <img decoding=\"async\" class=\"VignetteImg\" border=\"0\" src=\"https:\/\/thumb.ccsd.cnrs.fr\/8469814\/thumb\/little\" alt=\"\" \/><\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">titre<\/dt>\n<dd class=\"ValeurResAvecVignette Titre\"><a href=\"https:\/\/inserm.hal.science\/inserm-02146700v1\" target=\"_blank\" >Atlases of cognition with large-scale human brain mapping<\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">auteur<\/dt>\n<dd class=\"ValeurResAvecVignette Auteurs\">Ga\u00ebl Varoquaux, Yannick Schwartz, Russell A Poldrack, Baptiste Gauthier, Danilo Bzdok, Jean-Baptiste Poline, Bertrand Thirion<\/dd>\n<dt class=\"ChampResAvecVignette\">article<\/dt>\n<dd class=\"ValeurResAvecVignette article\"><i>PLoS Computational Biology<\/i>, 2018, 14 (11), pp.e1006565. <a target=\"_blank\" href=\"https:\/\/dx.doi.org\/10.1371\/journal.pcbi.1006565\">&#x27E8;10.1371\/journal.pcbi.1006565&#x27E9;<\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">Resume_court<\/dt>\n<dd class=\"ValeurResAvecVignette Debut_du_resume\">To map the neural substrate of mental function, cognitive neuroimaging relies on controlled psycholo &#8230;..<\/dd>\n<dt class=\"ChampResAvecVignette\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurResAvecVignette Fichier_joint\"> <a href=\"https:\/\/inserm.hal.science\/inserm-02146700\/file\/journal.pcbi.1006565.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/inserm.hal.science\/inserm-02146700\/file\/journal.pcbi.1006565.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/inserm.hal.science\/inserm-02146700\/file\/journal.pcbi.1006565.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/inserm.hal.science\/inserm-02146700v1\/bibtex\" target=\"_self\"> <img decoding=\"async\" alt=\"BibTex\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_bibtex3.png\" border=\"0\"  title=\"BibTex\" \/><\/a> <\/span><\/dd>\n<\/dl>\n<dl class='NoticeResAvecVignette'>\n<dd class='Vignette'> <a href=\"https:\/\/inria.hal.science\/hal-01806175v1\" target=\"_blank\"> <img decoding=\"async\" class=\"VignetteImg\" border=\"0\" src=\"https:\/\/thumb.ccsd.cnrs.fr\/8317514\/thumb\/little\" alt=\"\" \/><\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">titre<\/dt>\n<dd class=\"ValeurResAvecVignette Titre\"><a href=\"https:\/\/inria.hal.science\/hal-01806175v1\" target=\"_blank\" >Similarity encoding for learning with dirty categorical variables<\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">auteur<\/dt>\n<dd class=\"ValeurResAvecVignette Auteurs\">Patricio Cerda, Ga\u00ebl Varoquaux, Bal\u00e1zs K\u00e9gl<\/dd>\n<dt class=\"ChampResAvecVignette\">article<\/dt>\n<dd class=\"ValeurResAvecVignette article\"><i>Machine Learning<\/i>, 2018, <a target=\"_blank\" href=\"https:\/\/dx.doi.org\/10.1007\/s10994-018-5724-2\">&#x27E8;10.1007\/s10994-018-5724-2&#x27E9;<\/a><\/dd>\n<dt class=\"ChampResAvecVignette\">Resume_court<\/dt>\n<dd class=\"ValeurResAvecVignette Debut_du_resume\">For statistical learning, categorical variables in a table are usually considered as discrete entiti &#8230;..<\/dd>\n<dt class=\"ChampResAvecVignette\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurResAvecVignette Fichier_joint\"> <a href=\"https:\/\/inria.hal.science\/hal-01806175\/file\/article_hal.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/inria.hal.science\/hal-01806175\/file\/article_hal.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/inria.hal.science\/hal-01806175\/file\/article_hal.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/inria.hal.science\/hal-01806175v1\/bibtex\" target=\"_self\"> <img decoding=\"async\" alt=\"BibTex\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_bibtex3.png\" border=\"0\"  title=\"BibTex\" \/><\/a> <\/span><\/dd>\n<\/dl><\/div>\n<p> <\/body> <\/html> <\/p>\n","protected":false},"excerpt":{"rendered":"<p>Publications HAL du projet ANR. ANR-17-CE23-0018 2024 Journal articles titre On the consistency of supervised learning with missing values auteur Julie Josse, Jacob M. Chen, Nicolas Prost, Ga\u00ebl Varoquaux, Erwan Scornet article Statistical Papers, 2024, 65 (9), pp.5447-5479. &#x27E8;10.1007\/s00362-024-01550-4&#x27E9; Resume_court In many application settings, the data have missing entries which\u2026<\/p>\n<p> <a class=\"continue-reading-link\" href=\"https:\/\/project.inria.fr\/dirtydata\/publications\/\"><span>Continue reading<\/span><i class=\"crycon-right-dir\"><\/i><\/a> <\/p>\n","protected":false},"author":1155,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-63","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/project.inria.fr\/dirtydata\/wp-json\/wp\/v2\/pages\/63","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/project.inria.fr\/dirtydata\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/project.inria.fr\/dirtydata\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/project.inria.fr\/dirtydata\/wp-json\/wp\/v2\/users\/1155"}],"replies":[{"embeddable":true,"href":"https:\/\/project.inria.fr\/dirtydata\/wp-json\/wp\/v2\/comments?post=63"}],"version-history":[{"count":9,"href":"https:\/\/project.inria.fr\/dirtydata\/wp-json\/wp\/v2\/pages\/63\/revisions"}],"predecessor-version":[{"id":191,"href":"https:\/\/project.inria.fr\/dirtydata\/wp-json\/wp\/v2\/pages\/63\/revisions\/191"}],"wp:attachment":[{"href":"https:\/\/project.inria.fr\/dirtydata\/wp-json\/wp\/v2\/media?parent=63"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}