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We show how it is possible to use the Kohonen self-organizing algorithm to deal with data which contain missing values and to estimate them. After a methodological recall, we illustrate our purpose ...
Calcul de la vitesse de convergence dans le theoreme central limite vis a vis des distances de Prohorov, Dudley et Levy dans le cas de variables aleatoires dependantes
Entropie des processus lineaires
Comparaison et non-confluence des solutions d'equations differentielles stochastiques unidimensionelles
Methodes de changement de temps pour la convergence en loi des martingales
We study the maximum entropy method on the mean developed in 141 to reconstruçt a density under linear and non-linear convex constraints. We extend the procedure to the case of a locally con...
Approximation du temps local des champs aleatoires gaussiens stationnaires par regularisation des trajectoires
Inegalites de trace pour des matrices de Toeplitz et applications a des vraisemblances gaussiennes
We extend a classical property of the gaussian random functions to the gaussiau cbaoses of order two: Let X bc a gaussian real chaos of order two on a metrizable compact set 7: assume X is as. cont...
We extend a theorem due to Fernique [4]: let X be a Gaussian real chaos of finite degree on a metriç compact set T Suppose that X is continuous in probability and as. continuous along 9, whe...
In this paper we prove the pathwise uniqueness of solutions of a stochastic differential equation with a singular drift whiçh depends on time. Our method is of probabilistic nature, and it is...
We study the pathwise uniqueness of a one-dimension- , al stochastic differential equation driven by white noise and involving local time of the unknown process. We introduce a very weak condition ...
Founded in 1946, The Canadian Library Association/Association canadienne des bibliothèques was incorporated under the Companies Act on November 26, 1947. CLA/ACB is a national, not-for-profit, volunta...
This note proposes a new methodology for function classification with Support Vector Machine (SVM). Rather than relying on projection on a truncated Hilbert basis as in our previous work, we use an im...

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