Atelier des doctorants du jeudi 20 février
Disturbance observers in control
Disturbance observers in control
(annulé - COVID19)
On kernel estimation for spatial data.
In this talk, we present a central limit theorem for the well-known Nadaraya-Watson regression estimator in the context of strongly mixing and weakly dependent random fields in the sense of Rosenblatt (1956) and Wu (2005) respectively. Our main motivation is to provide mild conditions on the mixing coefficients and bandwidth parameters for the estimator to be asymptotically normal. We also present our current research concerning the recursive version of this estimator under the same conditions.
(annulé - COVID19)
Rigidité et disjonction de Möbius de systèmes dynamiques
La conjecture de Sarnak dit que tout système dynamique déterministe $(X,T)$ est disjoint (au sens arithmétique) de la fonction de Möbius $\mu$: $$\lim_{N\to\infty}\frac1N\sum_{n\leq N}f(T^nx)\mu(n)=0$$ pour toute fonction continue $f$ et tout $x\in X$. Les systèmes rigides sont déterministes, mais la rigidité peut être définie soit de façon topologique, soit métrique en utilisant les systèmes dynamiques métriques $(X,\nu,T)$ où $\nu$ parcurt l'ensemble des mesures $T$-invariantes.
In this talk we study high dimensional ergodic diffusion models in nonparametric setting on the basis of discrete data, when the diffusion coefficients are unknown. For this problem, by using efficient sequential point-wise estimators we construct a model selection procedure and then we show sharp oracle inequalities, i.e. the inequalities in which the main term coefficient is closed to one. This means that the proposed sequential model selection procedure is optimal in this sense.
(annulé - COVID19)
Sur l'inégalité isopérimétrique quantitative dans le plan
Limiting spectrum of sparse graphs
In this introductory talk, I will present a general limiting
theory for the spectrum of large networks. The models I will consider
are quite general, but they share a common feature : all of them are
studied in their very sparse regime where the number of connections has
the same order as the number of nodes (Erdös-Rényi with fixed mean
degree, regular graphs, uniform trees, uniform triangulations,
preferential attachments). The spectrum of such networks is notoriously
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de la Fédération Normandie-Mathématiques.
© 2025, Laboratoire de Mathématiques Raphaël Salem