

{"id":54,"date":"2014-10-20T17:12:10","date_gmt":"2014-10-20T15:12:10","guid":{"rendered":"https:\/\/project.inria.fr\/ExTra-Learn\/?page_id=54"},"modified":"2017-06-09T10:48:20","modified_gmt":"2017-06-09T08:48:20","slug":"publications","status":"publish","type":"page","link":"https:\/\/project.inria.fr\/ExTra-Learn\/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\/VisuRubriqueEncadre.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.  Extra-learn<\/title> <\/head> <body> <\/p>\n<div id=\"res_script\">\n<p class='Rubrique'>2020<\/p>\n<p class='SousRubrique'>Journal articles<\/p>\n<dl class='NoticeRes'>\n<dt class=\"ChampRes\">ref_biblio<\/dt>\n<dd class=\"ValeurRes ref_biblio\">Tom\u00e1\u0161 Koc\u00e1k, R\u00e9mi Munos, Branislav Kveton, Shipra Agrawal, Michal Valko. Spectral bandits. <i>Journal of Machine Learning Research<\/i>, 2020. <a target=\"_blank\" href=\"https:\/\/inria.hal.science\/hal-03084249v1\">&#x27E8;hal-03084249&#x27E9;<\/a><\/dd>\n<dt class=\"ChampRes\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurRes Fichier_joint\"> <a href=\"https:\/\/inria.hal.science\/hal-03084249\/file\/kocak2020spectral.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/inria.hal.science\/hal-03084249\/file\/kocak2020spectral.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/inria.hal.science\/hal-03084249\/file\/kocak2020spectral.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/inria.hal.science\/hal-03084249v1\/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='NoticeRes'>\n<dt class=\"ChampRes\">ref_biblio<\/dt>\n<dd class=\"ValeurRes ref_biblio\">Peter Bartlett, Victor Gabillon, Michal Valko. A simple parameter-free and adaptive approach to optimization under a minimal local smoothness assumption. <i>Algorithmic Learning Theory<\/i>, 2019, Chicago, United States. <a target=\"_blank\" href=\"https:\/\/inria.hal.science\/hal-01885368v2\">&#x27E8;hal-01885368v2&#x27E9;<\/a><\/dd>\n<dt class=\"ChampRes\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurRes Fichier_joint\"> <a href=\"https:\/\/inria.hal.science\/hal-01885368\/file\/bartlett2019simple.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/inria.hal.science\/hal-01885368\/file\/bartlett2019simple.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/inria.hal.science\/hal-01885368\/file\/bartlett2019simple.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/inria.hal.science\/hal-01885368v2\/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='NoticeRes'>\n<dt class=\"ChampRes\">ref_biblio<\/dt>\n<dd class=\"ValeurRes ref_biblio\">Xuedong Shang, Emilie Kaufmann, Michal Valko. General parallel optimization without a metric. <i>Algorithmic Learning Theory<\/i>, 2019, Chicago, United States. <a target=\"_blank\" href=\"https:\/\/inria.hal.science\/hal-02047225v2\">&#x27E8;hal-02047225v2&#x27E9;<\/a><\/dd>\n<dt class=\"ChampRes\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurRes Fichier_joint\"> <a href=\"https:\/\/inria.hal.science\/hal-02047225\/file\/shang2019general.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/inria.hal.science\/hal-02047225\/file\/shang2019general.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/inria.hal.science\/hal-02047225\/file\/shang2019general.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/inria.hal.science\/hal-02047225v2\/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'>Theses<\/p>\n<dl class='NoticeRes'>\n<dt class=\"ChampRes\">ref_biblio<\/dt>\n<dd class=\"ValeurRes ref_biblio\">Ronan Fruit. Exploration-exploitation dilemma in Reinforcement Learning under various form of prior knowledge. Artificial Intelligence [cs.AI]. Universit\u00e9 de Lille 1, Sciences et Technologies; CRIStAL UMR 9189, 2019. English. <a target=\"_blank\" href=\"https:\/\/www.theses.fr\/\">&#x27E8;NNT : &#x27E9;<\/a>. <a target=\"_blank\" href=\"https:\/\/theses.hal.science\/tel-02388395v2\">&#x27E8;tel-02388395v2&#x27E9;<\/a><\/dd>\n<dt class=\"ChampRes\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurRes Fichier_joint\"> <a href=\"https:\/\/theses.hal.science\/tel-02388395\/file\/main.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/theses.hal.science\/tel-02388395\/file\/main.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/theses.hal.science\/tel-02388395\/file\/main.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/theses.hal.science\/tel-02388395v2\/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'>Conference papers<\/p>\n<dl class='NoticeRes'>\n<dt class=\"ChampRes\">ref_biblio<\/dt>\n<dd class=\"ValeurRes ref_biblio\">Ronan Fruit, Matteo Pirotta, Alessandro Lazaric. Near Optimal Exploration-Exploitation in Non-Communicating Markov Decision Processes. <i>32nd Conference on Neural Information Processing Systems<\/i>, Dec 2018, Montr\u00e9al, Canada. <a target=\"_blank\" href=\"https:\/\/inria.hal.science\/hal-01941220v1\">&#x27E8;hal-01941220&#x27E9;<\/a><\/dd>\n<dt class=\"ChampRes\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurRes Fichier_joint\"> <a href=\"https:\/\/inria.hal.science\/hal-01941220\/file\/tucrl.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/inria.hal.science\/hal-01941220\/file\/tucrl.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/inria.hal.science\/hal-01941220\/file\/tucrl.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/inria.hal.science\/hal-01941220v1\/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='NoticeRes'>\n<dt class=\"ChampRes\">ref_biblio<\/dt>\n<dd class=\"ValeurRes ref_biblio\">Xuedong Shang, Emilie Kaufmann, Michal Valko. Adaptive black-box optimization got easier: HCT only needs local smoothness. <i>European Workshop on Reinforcement Learning<\/i>, Oct 2018, Lille, France. <a target=\"_blank\" href=\"https:\/\/inria.hal.science\/hal-01874637v1\">&#x27E8;hal-01874637&#x27E9;<\/a><\/dd>\n<dt class=\"ChampRes\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurRes Fichier_joint\"> <a href=\"https:\/\/inria.hal.science\/hal-01874637\/file\/shang2018adaptive.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/inria.hal.science\/hal-01874637\/file\/shang2018adaptive.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/inria.hal.science\/hal-01874637\/file\/shang2018adaptive.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/inria.hal.science\/hal-01874637v1\/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='NoticeRes'>\n<dt class=\"ChampRes\">ref_biblio<\/dt>\n<dd class=\"ValeurRes ref_biblio\">Matteo Papini, Damiano Binaghi, Giuseppe Canonaco, Matteo Pirotta, Marcello Restelli. Stochastic Variance-Reduced Policy Gradient. <i>ICML 2018 &#8211; 35th International Conference on Machine Learning<\/i>, Jul 2018, Stockholm, Sweden. pp.4026-4035. <a target=\"_blank\" href=\"https:\/\/inria.hal.science\/hal-01940394v1\">&#x27E8;hal-01940394&#x27E9;<\/a><\/dd>\n<dt class=\"ChampRes\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurRes Fichier_joint\"> <a href=\"https:\/\/inria.hal.science\/hal-01940394\/file\/supplementary.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/inria.hal.science\/hal-01940394\/file\/supplementary.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/inria.hal.science\/hal-01940394\/file\/supplementary.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/inria.hal.science\/hal-01940394v1\/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='NoticeRes'>\n<dt class=\"ChampRes\">ref_biblio<\/dt>\n<dd class=\"ValeurRes ref_biblio\">Ronan Fruit, Matteo Pirotta, Alessandro Lazaric, Ronald Ortner. Efficient Bias-Span-Constrained Exploration-Exploitation in Reinforcement Learning. <i>ICML 2018 &#8211; The 35th International Conference on Machine Learning<\/i>, Jul 2018, Stockholm, Sweden. pp.1578-1586. <a target=\"_blank\" href=\"https:\/\/inria.hal.science\/hal-01941206v1\">&#x27E8;hal-01941206&#x27E9;<\/a><\/dd>\n<dt class=\"ChampRes\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurRes Fichier_joint\"> <a href=\"https:\/\/inria.hal.science\/hal-01941206\/file\/fruit18a-supp.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/inria.hal.science\/hal-01941206\/file\/fruit18a-supp.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/inria.hal.science\/hal-01941206\/file\/fruit18a-supp.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/inria.hal.science\/hal-01941206v1\/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='NoticeRes'>\n<dt class=\"ChampRes\">ref_biblio<\/dt>\n<dd class=\"ValeurRes ref_biblio\">Andrea Tirinzoni, Andrea Sessa, Matteo Pirotta, Marcello Restelli. Importance Weighted Transfer of Samples in Reinforcement Learning. <i>ICML 2018 &#8211; The 35th International Conference on Machine Learning<\/i>, Jul 2018, Stockholm, Sweden. pp.4936-4945. <a target=\"_blank\" href=\"https:\/\/inria.hal.science\/hal-01941213v1\">&#x27E8;hal-01941213&#x27E9;<\/a><\/dd>\n<dt class=\"ChampRes\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurRes Fichier_joint\"> <a href=\"https:\/\/inria.hal.science\/hal-01941213\/file\/tirinzoni2018.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/inria.hal.science\/hal-01941213\/file\/tirinzoni2018.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/inria.hal.science\/hal-01941213\/file\/tirinzoni2018.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/inria.hal.science\/hal-01941213v1\/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='NoticeRes'>\n<dt class=\"ChampRes\">ref_biblio<\/dt>\n<dd class=\"ValeurRes ref_biblio\">Yasin Abbasi-Yadkori, Peter Bartlett, Victor Gabillon, Alan Malek, Michal Valko. Best of both worlds: Stochastic &#038; adversarial best-arm identification. <i>Conference on Learning Theory<\/i>, 2018, Stockholm, Sweden. <a target=\"_blank\" href=\"https:\/\/inria.hal.science\/hal-01808948v6\">&#x27E8;hal-01808948v6&#x27E9;<\/a><\/dd>\n<dt class=\"ChampRes\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurRes Fichier_joint\"> <a href=\"https:\/\/inria.hal.science\/hal-01808948\/file\/bob_best_arm_correction2023.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/inria.hal.science\/hal-01808948\/file\/bob_best_arm_correction2023.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/inria.hal.science\/hal-01808948\/file\/bob_best_arm_correction2023.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/inria.hal.science\/hal-01808948v6\/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'>2017<\/p>\n<p class='SousRubrique'>Conference papers<\/p>\n<dl class='NoticeRes'>\n<dt class=\"ChampRes\">ref_biblio<\/dt>\n<dd class=\"ValeurRes ref_biblio\">Ronan Fruit, Matteo Pirotta, Alessandro Lazaric, Emma Brunskill. Regret Minimization in MDPs with Options without Prior Knowledge. <i> NIPS 2017 &#8211; Neural Information Processing Systems<\/i>, Dec 2017, Long Beach, United States. pp.1-36. <a target=\"_blank\" href=\"https:\/\/inria.hal.science\/hal-01649082v1\">&#x27E8;hal-01649082&#x27E9;<\/a><\/dd>\n<dt class=\"ChampRes\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurRes Fichier_joint\"> <a href=\"https:\/\/inria.hal.science\/hal-01649082\/file\/supplementary.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/inria.hal.science\/hal-01649082\/file\/supplementary.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/inria.hal.science\/hal-01649082\/file\/supplementary.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/inria.hal.science\/hal-01649082v1\/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='NoticeRes'>\n<dt class=\"ChampRes\">ref_biblio<\/dt>\n<dd class=\"ValeurRes ref_biblio\">Carlos Riquelme, Mohammad Ghavamzadeh, Alessandro Lazaric. Active Learning for Accurate Estimation of Linear Models. <i>ICML 2017 &#8211; 34th International Conference on Machine Learning<\/i>, Aug 2017, Sydney, Australia. pp.36. <a target=\"_blank\" href=\"https:\/\/inria.hal.science\/hal-01538762v1\">&#x27E8;hal-01538762&#x27E9;<\/a><\/dd>\n<dt class=\"ChampRes\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurRes Fichier_joint\"> <a href=\"https:\/\/inria.hal.science\/hal-01538762\/file\/active_learning_accurate_estimation_linear_models_supplementary.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/inria.hal.science\/hal-01538762\/file\/active_learning_accurate_estimation_linear_models_supplementary.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/inria.hal.science\/hal-01538762\/file\/active_learning_accurate_estimation_linear_models_supplementary.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/inria.hal.science\/hal-01538762v1\/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='NoticeRes'>\n<dt class=\"ChampRes\">ref_biblio<\/dt>\n<dd class=\"ValeurRes ref_biblio\">Marc Abeille, Alessandro Lazaric. Linear Thompson Sampling Revisited. <i>AISTATS 2017 &#8211; 20th International Conference on Artificial Intelligence and Statistics<\/i>, Apr 2017, Fort Lauderdale, United States. <a target=\"_blank\" href=\"https:\/\/inria.hal.science\/hal-01493561v1\">&#x27E8;hal-01493561&#x27E9;<\/a><\/dd>\n<dt class=\"ChampRes\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurRes Fichier_joint\"> <a href=\"https:\/\/inria.hal.science\/hal-01493561\/file\/main.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/inria.hal.science\/hal-01493561\/file\/main.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/inria.hal.science\/hal-01493561\/file\/main.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/inria.hal.science\/hal-01493561v1\/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='NoticeRes'>\n<dt class=\"ChampRes\">ref_biblio<\/dt>\n<dd class=\"ValeurRes ref_biblio\">Ronan Fruit, Alessandro Lazaric. Exploration\u2013Exploitation in MDPs with Options. <i>AISTATS 2017 &#8211; 20th International Conference on Artificial Intelligence and Statistics<\/i>, Apr 2017, Fort Lauderdale, United States. <a target=\"_blank\" href=\"https:\/\/inria.hal.science\/hal-01493567v2\">&#x27E8;hal-01493567v2&#x27E9;<\/a><\/dd>\n<dt class=\"ChampRes\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurRes Fichier_joint\"> <a href=\"https:\/\/inria.hal.science\/hal-01493567\/file\/main.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/inria.hal.science\/hal-01493567\/file\/main.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/inria.hal.science\/hal-01493567\/file\/main.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/inria.hal.science\/hal-01493567v2\/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='NoticeRes'>\n<dt class=\"ChampRes\">ref_biblio<\/dt>\n<dd class=\"ValeurRes ref_biblio\">Marc Abeille, Alessandro Lazaric. Thompson Sampling for Linear-Quadratic Control Problems. <i>AISTATS 2017 &#8211; 20th International Conference on Artificial Intelligence and Statistics<\/i>, Apr 2017, Fort Lauderdale, United States. <a target=\"_blank\" href=\"https:\/\/inria.hal.science\/hal-01493564v1\">&#x27E8;hal-01493564&#x27E9;<\/a><\/dd>\n<dt class=\"ChampRes\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurRes Fichier_joint\"> <a href=\"https:\/\/inria.hal.science\/hal-01493564\/file\/main.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/inria.hal.science\/hal-01493564\/file\/main.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/inria.hal.science\/hal-01493564\/file\/main.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/inria.hal.science\/hal-01493564v1\/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='NoticeRes'>\n<dt class=\"ChampRes\">ref_biblio<\/dt>\n<dd class=\"ValeurRes ref_biblio\">Daniele Calandriello, Alessandro Lazaric, Michal Valko. Second-Order Kernel Online Convex Optimization with Adaptive Sketching. <i>International Conference on Machine Learning<\/i>, 2017, Sydney, Australia. <a target=\"_blank\" href=\"https:\/\/inria.hal.science\/hal-01537799v1\">&#x27E8;hal-01537799&#x27E9;<\/a><\/dd>\n<dt class=\"ChampRes\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurRes Fichier_joint\"> <a href=\"https:\/\/inria.hal.science\/hal-01537799\/file\/calandriello2017second-order.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/inria.hal.science\/hal-01537799\/file\/calandriello2017second-order.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/inria.hal.science\/hal-01537799\/file\/calandriello2017second-order.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/inria.hal.science\/hal-01537799v1\/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='NoticeRes'>\n<dt class=\"ChampRes\">ref_biblio<\/dt>\n<dd class=\"ValeurRes ref_biblio\">Daniele Calandriello, Alessandro Lazaric, Michal Valko. Efficient second-order online kernel learning with adaptive embedding. <i>Neural Information Processing Systems<\/i>, 2017, Long Beach, United States. <a target=\"_blank\" href=\"https:\/\/inria.hal.science\/hal-01643961v1\">&#x27E8;hal-01643961&#x27E9;<\/a><\/dd>\n<dt class=\"ChampRes\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurRes Fichier_joint\"> <a href=\"https:\/\/inria.hal.science\/hal-01643961\/file\/calandriello2017efficient.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/inria.hal.science\/hal-01643961\/file\/calandriello2017efficient.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/inria.hal.science\/hal-01643961\/file\/calandriello2017efficient.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/inria.hal.science\/hal-01643961v1\/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='NoticeRes'>\n<dt class=\"ChampRes\">ref_biblio<\/dt>\n<dd class=\"ValeurRes ref_biblio\">Guillaume Gautier, R\u00e9mi Bardenet, Michal Valko. Zonotope hit-and-run for efficient sampling from projection DPPs. <i>International Conference on Machine Learning<\/i>, 2017, Sydney, Australia. <a target=\"_blank\" href=\"https:\/\/inria.hal.science\/hal-01526577v2\">&#x27E8;hal-01526577v2&#x27E9;<\/a><\/dd>\n<dt class=\"ChampRes\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurRes Fichier_joint\"> <a href=\"https:\/\/inria.hal.science\/hal-01526577\/file\/gautier2017zonotope.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/inria.hal.science\/hal-01526577\/file\/gautier2017zonotope.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/inria.hal.science\/hal-01526577\/file\/gautier2017zonotope.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/inria.hal.science\/hal-01526577v2\/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='NoticeRes'>\n<dt class=\"ChampRes\">ref_biblio<\/dt>\n<dd class=\"ValeurRes ref_biblio\">Daniele Calandriello, Alessandro Lazaric, Michal Valko. Distributed adaptive sampling for kernel matrix approximation. <i>International Conference on Artificial Intelligence and Statistics<\/i>, 2017, Fort Lauderdale, United States. <a target=\"_blank\" href=\"https:\/\/inria.hal.science\/hal-01482760v1\">&#x27E8;hal-01482760&#x27E9;<\/a><\/dd>\n<dt class=\"ChampRes\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurRes Fichier_joint\"> <a href=\"https:\/\/inria.hal.science\/hal-01482760\/file\/calandriello2017distributed.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/inria.hal.science\/hal-01482760\/file\/calandriello2017distributed.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/inria.hal.science\/hal-01482760\/file\/calandriello2017distributed.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/inria.hal.science\/hal-01482760v1\/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='NoticeRes'>\n<dt class=\"ChampRes\">ref_biblio<\/dt>\n<dd class=\"ValeurRes ref_biblio\">Akram Erraqabi, Alessandro Lazaric, Michal Valko, Emma Brunskill, Yun-En Liu. Trading off rewards and errors in multi-armed bandits. <i>International Conference on Artificial Intelligence and Statistics<\/i>, 2017, Fort Lauderdale, United States. <a target=\"_blank\" href=\"https:\/\/inria.hal.science\/hal-01482765v1\">&#x27E8;hal-01482765&#x27E9;<\/a><\/dd>\n<dt class=\"ChampRes\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurRes Fichier_joint\"> <a href=\"https:\/\/inria.hal.science\/hal-01482765\/file\/erraqabi2017trading.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/inria.hal.science\/hal-01482765\/file\/erraqabi2017trading.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/inria.hal.science\/hal-01482765\/file\/erraqabi2017trading.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/inria.hal.science\/hal-01482765v1\/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'>2016<\/p>\n<p class='SousRubrique'>Conference papers<\/p>\n<dl class='NoticeRes'>\n<dt class=\"ChampRes\">ref_biblio<\/dt>\n<dd class=\"ValeurRes ref_biblio\">Jean-Bastien Grill, Michal Valko, R\u00e9mi Munos. Blazing the trails before beating the path: Sample-efficient Monte-Carlo planning. <i>Neural Information Processing Systems<\/i>, Dec 2016, Barcelona, Spain. <a target=\"_blank\" href=\"https:\/\/inria.hal.science\/hal-01389107v3\">&#x27E8;hal-01389107v3&#x27E9;<\/a><\/dd>\n<dt class=\"ChampRes\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurRes Fichier_joint\"> <a href=\"https:\/\/inria.hal.science\/hal-01389107\/file\/grill2016blazing.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/inria.hal.science\/hal-01389107\/file\/grill2016blazing.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/inria.hal.science\/hal-01389107\/file\/grill2016blazing.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/inria.hal.science\/hal-01389107v3\/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='NoticeRes'>\n<dt class=\"ChampRes\">ref_biblio<\/dt>\n<dd class=\"ValeurRes ref_biblio\">Daniele Calandriello, Alessandro Lazaric, Michal Valko. Analysis of Nystr\u00f6m method with sequential ridge leverage score sampling. <i>Uncertainty in Artificial Intelligence<\/i>, Jun 2016, New York City, United States. <a target=\"_blank\" href=\"https:\/\/inria.hal.science\/hal-01343674v1\">&#x27E8;hal-01343674&#x27E9;<\/a><\/dd>\n<dt class=\"ChampRes\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurRes Fichier_joint\"> <a href=\"https:\/\/inria.hal.science\/hal-01343674\/file\/calandriello2016analysis.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/inria.hal.science\/hal-01343674\/file\/calandriello2016analysis.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/inria.hal.science\/hal-01343674\/file\/calandriello2016analysis.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/inria.hal.science\/hal-01343674v1\/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='NoticeRes'>\n<dt class=\"ChampRes\">ref_biblio<\/dt>\n<dd class=\"ValeurRes ref_biblio\">Tom\u00e1\u0161 Koc\u00e1k, Gergely Neu, Michal Valko. Online learning with Erd\u0151s-R\u00e9nyi side-observation graphs. <i>Uncertainty in Artificial Intelligence<\/i>, Jun 2016, New York City, United States. <a target=\"_blank\" href=\"https:\/\/inria.hal.science\/hal-01320588v1\">&#x27E8;hal-01320588&#x27E9;<\/a><\/dd>\n<dt class=\"ChampRes\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurRes Fichier_joint\"> <a href=\"https:\/\/inria.hal.science\/hal-01320588\/file\/kocak2016onlinea.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/inria.hal.science\/hal-01320588\/file\/kocak2016onlinea.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/inria.hal.science\/hal-01320588\/file\/kocak2016onlinea.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/inria.hal.science\/hal-01320588v1\/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='NoticeRes'>\n<dt class=\"ChampRes\">ref_biblio<\/dt>\n<dd class=\"ValeurRes ref_biblio\">Akram Erraqabi, Michal Valko, Alexandra Carpentier, Odalric-Ambrym Maillard. Pliable rejection sampling. <i>International Conference on Machine Learning<\/i>, Jun 2016, New York City, United States. <a target=\"_blank\" href=\"https:\/\/inria.hal.science\/hal-01322168v1\">&#x27E8;hal-01322168&#x27E9;<\/a><\/dd>\n<dt class=\"ChampRes\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurRes Fichier_joint\"> <a href=\"https:\/\/inria.hal.science\/hal-01322168\/file\/erraqabi2016pliable.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/inria.hal.science\/hal-01322168\/file\/erraqabi2016pliable.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/inria.hal.science\/hal-01322168\/file\/erraqabi2016pliable.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/inria.hal.science\/hal-01322168v1\/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='NoticeRes'>\n<dt class=\"ChampRes\">ref_biblio<\/dt>\n<dd class=\"ValeurRes ref_biblio\">Kamyar Azizzadenesheli, Alessandro Lazaric, Animashree Anandkumar. Reinforcement Learning of POMDPs using Spectral Methods. <i>Proceedings of the 29th Annual Conference on Learning Theory (COLT2016)<\/i>, Jun 2016, New York City, United States. <a target=\"_blank\" href=\"https:\/\/inria.hal.science\/hal-01322207v1\">&#x27E8;hal-01322207&#x27E9;<\/a><\/dd>\n<dt class=\"ChampRes\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurRes Fichier_joint\"> <a href=\"https:\/\/inria.hal.science\/hal-01322207\/file\/master.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/inria.hal.science\/hal-01322207\/file\/master.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/inria.hal.science\/hal-01322207\/file\/master.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/inria.hal.science\/hal-01322207v1\/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='NoticeRes'>\n<dt class=\"ChampRes\">ref_biblio<\/dt>\n<dd class=\"ValeurRes ref_biblio\">Tom\u00e1\u0161 Koc\u00e1k, Gergely Neu, Michal Valko. Online learning with noisy side observations. <i>International Conference on Artificial Intelligence and Statistics<\/i>, May 2016, Seville, Spain. <a target=\"_blank\" href=\"https:\/\/inria.hal.science\/hal-01303377v1\">&#x27E8;hal-01303377&#x27E9;<\/a><\/dd>\n<dt class=\"ChampRes\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurRes Fichier_joint\"> <a href=\"https:\/\/inria.hal.science\/hal-01303377\/file\/kocak2016online.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/inria.hal.science\/hal-01303377\/file\/kocak2016online.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/inria.hal.science\/hal-01303377\/file\/kocak2016online.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/inria.hal.science\/hal-01303377v1\/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='NoticeRes'>\n<dt class=\"ChampRes\">ref_biblio<\/dt>\n<dd class=\"ValeurRes ref_biblio\">Alexandra Carpentier, Michal Valko. Revealing graph bandits for maximizing local influence. <i>International Conference on Artificial Intelligence and Statistics<\/i>, May 2016, Seville, Spain. <a target=\"_blank\" href=\"https:\/\/inria.hal.science\/hal-01304020v3\">&#x27E8;hal-01304020v3&#x27E9;<\/a><\/dd>\n<dt class=\"ChampRes\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurRes Fichier_joint\"> <a href=\"https:\/\/inria.hal.science\/hal-01304020\/file\/carpentier2016revealing.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/inria.hal.science\/hal-01304020\/file\/carpentier2016revealing.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/inria.hal.science\/hal-01304020\/file\/carpentier2016revealing.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/inria.hal.science\/hal-01304020v3\/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='NoticeRes'>\n<dt class=\"ChampRes\">ref_biblio<\/dt>\n<dd class=\"ValeurRes ref_biblio\">Victor Gabillon, Alessandro Lazaric, Mohammad Ghavamzadeh, Ronald Ortner, Peter Bartlett. Improved Learning Complexity in Combinatorial Pure Exploration Bandits. <i>Proceedings of the 19th International Conference on Artificial Intelligence (AISTATS)<\/i>, May 2016, Cadiz, Spain. <a target=\"_blank\" href=\"https:\/\/inria.hal.science\/hal-01322198v1\">&#x27E8;hal-01322198&#x27E9;<\/a><\/dd>\n<dt class=\"ChampRes\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurRes Fichier_joint\"> <a href=\"https:\/\/inria.hal.science\/hal-01322198\/file\/AISTATS_full_CR.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/inria.hal.science\/hal-01322198\/file\/AISTATS_full_CR.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/inria.hal.science\/hal-01322198\/file\/AISTATS_full_CR.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/inria.hal.science\/hal-01322198v1\/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'>2015<\/p>\n<p class='SousRubrique'>Conference papers<\/p>\n<dl class='NoticeRes'>\n<dt class=\"ChampRes\">ref_biblio<\/dt>\n<dd class=\"ValeurRes ref_biblio\">Jessica Chemali, Alessandro Lazaric. Direct Policy Iteration with Demonstrations. <i>IJCAI &#8211; 24th International Joint Conference on Artificial Intelligence<\/i>, Jul 2015, Buenos Aires, Argentina. <a target=\"_blank\" href=\"https:\/\/inria.hal.science\/hal-01237659v1\">&#x27E8;hal-01237659&#x27E9;<\/a><\/dd>\n<dt class=\"ChampRes\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurRes Fichier_joint\"> <a href=\"https:\/\/inria.hal.science\/hal-01237659\/file\/DPID_CameraReady.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/inria.hal.science\/hal-01237659\/file\/DPID_CameraReady.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/inria.hal.science\/hal-01237659\/file\/DPID_CameraReady.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/inria.hal.science\/hal-01237659v1\/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='NoticeRes'>\n<dt class=\"ChampRes\">ref_biblio<\/dt>\n<dd class=\"ValeurRes ref_biblio\">Julien Audiffren, Michal Valko, Alessandro Lazaric, Mohammad Ghavamzadeh. Maximum Entropy Semi-Supervised Inverse Reinforcement Learning. <i>International Joint Conference on Artificial Intelligence<\/i>, Jul 2015, Bueons Aires, Argentina. <a target=\"_blank\" href=\"https:\/\/inria.hal.science\/hal-01146187v1\">&#x27E8;hal-01146187&#x27E9;<\/a><\/dd>\n<dt class=\"ChampRes\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurRes Fichier_joint\"> <a href=\"https:\/\/inria.hal.science\/hal-01146187\/file\/messi-TR.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/inria.hal.science\/hal-01146187\/file\/messi-TR.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/inria.hal.science\/hal-01146187\/file\/messi-TR.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/inria.hal.science\/hal-01146187v1\/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='NoticeRes'>\n<dt class=\"ChampRes\">ref_biblio<\/dt>\n<dd class=\"ValeurRes ref_biblio\">Daniele Calandriello, Alessandro Lazaric, Michal Valko. Large-scale semi-supervised learning with online spectral graph sparsification. <i>Resource-Efficient Machine Learning workshop at International Conference on Machine Learning<\/i>, Jul 2015, Lille, France. <a target=\"_blank\" href=\"https:\/\/inria.hal.science\/hal-01544929v1\">&#x27E8;hal-01544929&#x27E9;<\/a><\/dd>\n<dt class=\"ChampRes\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurRes Fichier_joint\"> <a href=\"https:\/\/inria.hal.science\/hal-01544929\/file\/calandriello2015large-scale.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/inria.hal.science\/hal-01544929\/file\/calandriello2015large-scale.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/inria.hal.science\/hal-01544929\/file\/calandriello2015large-scale.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/inria.hal.science\/hal-01544929v1\/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='NoticeRes'>\n<dt class=\"ChampRes\">ref_biblio<\/dt>\n<dd class=\"ValeurRes ref_biblio\">Alexandra Carpentier, Michal Valko. Simple regret for infinitely many armed bandits. <i>International Conference on Machine Learning<\/i>, Jul 2015, Lille, France. <a target=\"_blank\" href=\"https:\/\/inria.hal.science\/hal-01153538v1\">&#x27E8;hal-01153538&#x27E9;<\/a><\/dd>\n<dt class=\"ChampRes\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurRes Fichier_joint\"> <a href=\"https:\/\/inria.hal.science\/hal-01153538\/file\/carpentier2015simple.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/inria.hal.science\/hal-01153538\/file\/carpentier2015simple.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/inria.hal.science\/hal-01153538\/file\/carpentier2015simple.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/inria.hal.science\/hal-01153538v1\/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='NoticeRes'>\n<dt class=\"ChampRes\">ref_biblio<\/dt>\n<dd class=\"ValeurRes ref_biblio\">Jean-Bastien Grill, Michal Valko, R\u00e9mi Munos. Black-box optimization of noisy functions with unknown smoothness. <i>Neural Information Processing Systems<\/i>, 2015, Montr\u00e9al, Canada. <a target=\"_blank\" href=\"https:\/\/inria.hal.science\/hal-01222915v4\">&#x27E8;hal-01222915v4&#x27E9;<\/a><\/dd>\n<dt class=\"ChampRes\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurRes Fichier_joint\"> <a href=\"https:\/\/inria.hal.science\/hal-01222915\/file\/grill2015black-box.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/inria.hal.science\/hal-01222915\/file\/grill2015black-box.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/inria.hal.science\/hal-01222915\/file\/grill2015black-box.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/inria.hal.science\/hal-01222915v4\/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='NoticeRes'>\n<dt class=\"ChampRes\">ref_biblio<\/dt>\n<dd class=\"ValeurRes ref_biblio\">Manjesh Kumar Hanawal Hanawal, Venkatesh Saligrama, Michal Valko, R\u00e9mi Munos. Cheap Bandits. <i>International Conference on Machine Learning<\/i>, 2015, Lille, France. <a target=\"_blank\" href=\"https:\/\/inria.hal.science\/hal-01153540v1\">&#x27E8;hal-01153540&#x27E9;<\/a><\/dd>\n<dt class=\"ChampRes\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurRes Fichier_joint\"> <a href=\"https:\/\/inria.hal.science\/hal-01153540\/file\/hanawal2015cheap.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/inria.hal.science\/hal-01153540\/file\/hanawal2015cheap.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/inria.hal.science\/hal-01153540\/file\/hanawal2015cheap.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/inria.hal.science\/hal-01153540v1\/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'>2014<\/p>\n<p class='SousRubrique'>Conference papers<\/p>\n<dl class='NoticeRes'>\n<dt class=\"ChampRes\">ref_biblio<\/dt>\n<dd class=\"ValeurRes ref_biblio\">Daniele Calandriello, Alessandro Lazaric, Marcello Restelli. Sparse Multi-task Reinforcement Learning. <i>NIPS &#8211; Advances in Neural Information Processing Systems 26<\/i>, Dec 2014, Montreal, Canada. <a target=\"_blank\" href=\"https:\/\/inria.hal.science\/hal-01073513v1\">&#x27E8;hal-01073513&#x27E9;<\/a><\/dd>\n<dt class=\"ChampRes\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurRes Fichier_joint\"> <a href=\"https:\/\/inria.hal.science\/hal-01073513\/file\/sparse_mtrl_tech.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/inria.hal.science\/hal-01073513\/file\/sparse_mtrl_tech.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/inria.hal.science\/hal-01073513\/file\/sparse_mtrl_tech.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/inria.hal.science\/hal-01073513v1\/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='NoticeRes'>\n<dt class=\"ChampRes\">ref_biblio<\/dt>\n<dd class=\"ValeurRes ref_biblio\">Julien Audiffren, Michal Valko, Alessandro Lazaric, Mohammad Ghavamzadeh. MESSI: Maximum Entropy Semi-Supervised Inverse Reinforcement Learning. <i>NIPS Workshop on Novel Trends and Applications in Reinforcement Learning<\/i>, 2014, Montreal, Canada. <a target=\"_blank\" href=\"https:\/\/inria.hal.science\/hal-01177446v1\">&#x27E8;hal-01177446&#x27E9;<\/a><\/dd>\n<dt class=\"ChampRes\">Acc\u00e8s au texte int\u00e9gral et bibtex<\/dt>\n<dd class=\"ValeurRes Fichier_joint\"> <a href=\"https:\/\/inria.hal.science\/hal-01177446\/file\/audiffren2014messi.pdf\"  target=\"_blank\"> <img decoding=\"async\" alt=\"https:\/\/inria.hal.science\/hal-01177446\/file\/audiffren2014messi.pdf\" src=\"https:\/\/haltools.inria.fr\/images\/Haltools_pdf.png\" border=\"0\" title=\"https:\/\/inria.hal.science\/hal-01177446\/file\/audiffren2014messi.pdf\" \/><\/a> <span class=\"LienBibtexACoteFulltext\"><a href=\"https:\/\/inria.hal.science\/hal-01177446v1\/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. Extra-learn 2020 Journal articles ref_biblio Tom\u00e1\u0161 Koc\u00e1k, R\u00e9mi Munos, Branislav Kveton, Shipra Agrawal, Michal Valko. Spectral bandits. Journal of Machine Learning Research, 2020. &#x27E8;hal-03084249&#x27E9; Acc\u00e8s \u2026<\/p>\n<p class=\"continue-reading-button\"> <a class=\"continue-reading-link\" href=\"https:\/\/project.inria.fr\/ExTra-Learn\/publications\/\">Continue reading<i class=\"crycon-right-dir\"><\/i><\/a><\/p>\n","protected":false},"author":552,"featured_media":0,"parent":0,"menu_order":5,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-54","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/project.inria.fr\/ExTra-Learn\/wp-json\/wp\/v2\/pages\/54","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/project.inria.fr\/ExTra-Learn\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/project.inria.fr\/ExTra-Learn\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/project.inria.fr\/ExTra-Learn\/wp-json\/wp\/v2\/users\/552"}],"replies":[{"embeddable":true,"href":"https:\/\/project.inria.fr\/ExTra-Learn\/wp-json\/wp\/v2\/comments?post=54"}],"version-history":[{"count":21,"href":"https:\/\/project.inria.fr\/ExTra-Learn\/wp-json\/wp\/v2\/pages\/54\/revisions"}],"predecessor-version":[{"id":190,"href":"https:\/\/project.inria.fr\/ExTra-Learn\/wp-json\/wp\/v2\/pages\/54\/revisions\/190"}],"wp:attachment":[{"href":"https:\/\/project.inria.fr\/ExTra-Learn\/wp-json\/wp\/v2\/media?parent=54"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}