Literatura científica selecionada sobre o tema "Algorithme en ligne avec conseil"
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Artigos de revistas sobre o assunto "Algorithme en ligne avec conseil"
ADELINE-DUFLOT, F., E. FERRAT, S. BROSSIER, R. GAUZIT, R. COHEN e V. RENARD. "Conseil téléphonique en prescription antibiotique (CoTéPrAgmatique) auprès des médecins généralistes : résultats de deux ans de fonctionnement". EXERCER 32, n.º 176 (1 de outubro de 2021): 352–58. http://dx.doi.org/10.56746/exercer.2021.176.352.
Texto completo da fonteClarke, Graham. "Décisions rendues par le Conseil canadien des relations du travail". Relations industrielles 44, n.º 4 (12 de abril de 2005): 933–46. http://dx.doi.org/10.7202/050543ar.
Texto completo da fonteOh, Jiwon, Marie-Sarah Gagné-Brosseau, Melanie Guenette, Catherine Larochelle, François Lemieux, Suresh Menon, Sarah A. Morrow et al. "Toward a Shared-Care Model of Relapsing-Remitting Multiple Sclerosis: Role of the Primary Care Practitioner". Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques 45, n.º 3 (maio de 2018): 304–12. http://dx.doi.org/10.1017/cjn.2018.7.
Texto completo da fonteDouzon-Bernal, M. "Un dispositif global de soins des troubles de la relation mère–nourrisson". European Psychiatry 28, S2 (novembro de 2013): 57. http://dx.doi.org/10.1016/j.eurpsy.2013.09.149.
Texto completo da fonteSolère, Jean-Luc. "Bayle historien et critique du matérialisme dans le dictionnaire". Kriterion: Revista de Filosofia 50, n.º 120 (dezembro de 2009): 423–36. http://dx.doi.org/10.1590/s0100-512x2009000200010.
Texto completo da fontePéguret, Muriel, e Catherine Lamaison. "L’influence du Cadre européen commun de référence pour les langues (2001) sur l’enseignement du français langue seconde au niveau universitaire au Canada". La Revue de l’AQEFLS 33, n.º 1 (16 de setembro de 2021): 35–44. http://dx.doi.org/10.7202/1081268ar.
Texto completo da fonteChauvard, Jean-François. "Adaptabilité versus inaliénabilité Les dérogations des fidéicommis dans la Venise du XVIIIe siècle". Annales. Histoire, Sciences Sociales 70, n.º 04 (dezembro de 2015): 849–78. http://dx.doi.org/10.1353/ahs.2015.0199.
Texto completo da fonteNaji, Khadija, e Abdelali Ibriz. "Approach for Eliciting Learners' Preferences in Moocs Through Collaborative Filtering". International Journal of Emerging Technologies in Learning (iJET) 17, n.º 14 (26 de julho de 2022): 235–45. http://dx.doi.org/10.3991/ijet.v17i14.29887.
Texto completo da fonteALLEREAU, P., E. ALLORY e A. MAURY. "Les avis en ligne concernant les MG. Une étude par analyse de contenu en Ille-et-Vilaine". EXERCER 35, n.º 200 (1 de fevereiro de 2024): 64–69. http://dx.doi.org/10.56746/exercer.2024.200.64.
Texto completo da fonteVeall, Michael R. "Internationalization and the Internet: The Case of Canadian Public Policy/Analyse de politiques". Scholarly and Research Communication 11, n.º 1 (10 de março de 2020): 9. http://dx.doi.org/10.22230/src.2020v11n1a351.
Texto completo da fonteTeses / dissertações sobre o assunto "Algorithme en ligne avec conseil"
Jin, Shendan. "Online computation beyond standard models". Electronic Thesis or Diss., Sorbonne université, 2020. http://www.theses.fr/2020SORUS152.
Texto completo da fonteIn the standard setting of online computation, the input is not entirely available from the beginning, but is revealed incrementally, piece by piece, as a sequence of requests. Whenever a request arrives, the online algorithm has to make immediately irrevocable decisions to serve the request, without knowledge on the future requests. Usually, the standard framework to evaluate the performance of online algorithms is competitive analysis, which compares the worst-case performance of an online algorithm to an offline optimal solution. In this thesis, we will study some new ways of looking at online problems. First, we study the online computation in the recourse model, in which the irrevocability on online decisions is relaxed. In other words, the online algorithm is allowed to go back and change previously made decisions. More precisely, we show how to identify the trade-off between the number of re-optimization and the performance of online algorithms for the online maximum matching problem. Moreover, we study measures other than competitive analysis for evaluating the performance of online algorithms. We observe that sometimes, competitive analysis cannot distinguish the performance of different algorithms due to the worst-case nature of the competitive ratio. We demonstrate that a similar situation arises in the linear search problem. More precisely, we revisit the linear search problem and introduce a measure, which can be applied as a refinement of the competitive ratio. Last, we study the online computation in the advice model, in which the algorithm receives as input not only a sequence of requests, but also some advice on the request sequence. Specifically, we study a recent model with untrusted advice, in which the advice can be either trusted or untrusted. Assume that in the latter case, the advice can be generated from a malicious source. We show how to identify a Pareto optimal strategy for the online bidding problem in the untrusted advice model