Literatura científica selecionada sobre o tema "Données non identiquement distribuées"
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Artigos de revistas sobre o assunto "Données non identiquement distribuées"
Adlouni, Salaheddine El, e Taha B. M. J. Ouarda. "Comparaison des méthodes d’estimation des paramètres du modèle GEV non stationnaire". Revue des sciences de l'eau 21, n.º 1 (29 de abril de 2008): 35–50. http://dx.doi.org/10.7202/017929ar.
Texto completo da fonteAndreoli, Rémi, Benoît Ducarouge, Jonathan Maura, Audrey Leopold, Pierre-Nicolas Mougel, Arnaud Durand, Cyril Marchand et al. "L'imagerie spatiale à très haute résolution au coeur du dispositif de Geospatial Cloud Computing QëhnelöTM : application aux données Pléiades en Nouvelle-Calédonie." Revue Française de Photogrammétrie et de Télédétection, n.º 209 (11 de janeiro de 2015): 47–57. http://dx.doi.org/10.52638/rfpt.2015.185.
Texto completo da fonteBreithaupt, Sandrine, e Anne Clerc Georgy. "Que révèlent les situations d’évaluation de la posture en formation des futurs enseignants ?" Mesure et évaluation en éducation 40, n.º 2 (23 de fevereiro de 2018): 57–90. http://dx.doi.org/10.7202/1043568ar.
Texto completo da fonteBocquet, Marc. "Modélisation inverse des sources de pollution atmosphérique accidentelle : progrès récents". Pollution atmosphérique, NS 2 (1 de setembro de 2010): 151–60. http://dx.doi.org/10.54563/pollution-atmospherique.7144.
Texto completo da fonteCHILLIARD, Y., R. VERITE e A. PFLIMLIN. "Effets de la somatotropine bovine sur les performances des vaches laitières dans les conditions françaises d’élevage". INRAE Productions Animales 2, n.º 5 (10 de dezembro de 1989): 301–12. http://dx.doi.org/10.20870/productions-animales.1989.2.5.4423.
Texto completo da fonteHeyer, Éric. "Comment expliquer l’évolution de l’emploi salarié depuis la crise Covid ?" Revue de l'OFCE N° 180, n.º 1 (6 de março de 2024): 179–206. http://dx.doi.org/10.3917/reof.180.0179.
Texto completo da fonteRenaud, François. "Les motivations dans une organisation partisane de circonscription". Articles 14, n.º 1 (12 de abril de 2005): 59–79. http://dx.doi.org/10.7202/055602ar.
Texto completo da fonteTeses / dissertações sobre o assunto "Données non identiquement distribuées"
Hakam, Samir. "Convergences des statistiques d'ordre des variables aléatoires non identiquement distribuées. Convergences des statistiques d'ordre de rang intermédiaire et central". Paris 6, 1991. http://www.theses.fr/1991PA066515.
Texto completo da fonteDabo, Issa-Mbenard. "Applications de la théorie des matrices aléatoires en grandes dimensions et des probabilités libres en apprentissage statistique par réseaux de neurones". Electronic Thesis or Diss., Bordeaux, 2025. http://www.theses.fr/2025BORD0021.
Texto completo da fonteThe functioning of machine learning algorithms relies heavily on the structure of the data they are given to study. Most research work in machine learning focuses on the study of homogeneous data, often modeled by independent and identically distributed random variables. However, data encountered in practice are often heterogeneous. In this thesis, we propose to consider heterogeneous data by endowing them with a variance profile. This notion, derived from random matrix theory, allows us in particular to study data arising from mixture models. We are particularly interested in the problem of ridge regression through two models: the linear ridge model and the random feature ridge model. In this thesis, we study the performance of these two models in the high-dimensional regime, i.e., when the size of the training sample and the dimension of the data tend to infinity at comparable rates. To this end, we propose asymptotic equivalents for the training error and the test error associated with the models of interest. The derivation of these equivalents relies heavily on spectral analysis from random matrix theory, free probability theory, and traffic theory. Indeed, the performance measurement of many learning models depends on the distribution of the eigenvalues of random matrices. Moreover, these results enabled us to observe phenomena specific to the high-dimensional regime, such as the double descent phenomenon. Our theoretical study is accompanied by numerical experiments illustrating the accuracy of the asymptotic equivalents we provide
Charbonnier, Camille. "Inférence de réseaux de régulation génétique à partir de données du transcriptome non indépendamment et indentiquement distribuées". Thesis, Evry-Val d'Essonne, 2012. http://www.theses.fr/2012EVRY0022/document.
Texto completo da fonteThis thesis investigates the inference of high-dimensional Gaussian graphical models from non identically and independently distributed transcriptomic data in the objective of recovering gene regulatory networks. In the context of high-dimensional statistics, data heterogeneity paves the way to the definition of structured regularizers in order to improve the quality of the estimator. We first consider heterogeneity at the network level, building upon the assumption that biological networks are organized, which leads to the definition of a weighted l1 regularization. Modelling heterogeneity at the observation level, we provide a consistency analysis of a recent block-sparse regularizer called the cooperative-Lasso designed to combine observations from distinct but close datasets. Finally we address the crucial question of uncertainty, deriving homonegeity tests for high-dimensional linear regression
Fortin, Benoît. "Méthodes conjointes de détection et suivi basé-modèle de cibles distribuées par filtrage non-linéaire dans les données lidar à balayage". Phd thesis, Université du Littoral Côte d'Opale, 2013. http://tel.archives-ouvertes.fr/tel-01021085.
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