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We study a stochastic program where the probability distribution of the uncertain problem parameters is unknown and only indirectly observed via finitely many correlated samples generated by an unknown Markov chain with d states. We propose a data-driven d ...
This thesis focuses on two kinds of statistical inference problems in signal processing and data science. The first problem is the estimation of a structured informative tensor from the observation of a noisy tensor in which it is buried. The structure com ...
This paper addresses the mean-field behavior of large-scale systems of parallel servers with a processor sharing service discipline when arrivals are Poisson and jobs have general service time distributions when an SQ(d) routing policy is used. Under this ...
A combination of nanoscale imaging techniques such as atomic force microscopy and scanning electron microscopy are used to investigate the relationship between surface morphology and height statistics of GaN cap layers in InGaN/GaN light emitting diode het ...
We study mixing and diffusion properties of passive scalars driven by generic rough shear flows. Genericity is here understood in the sense of prevalence, and (ir)regularity is measured in the Besov-Nikolskii scale B\alpha 1,\infty, \alpha \in (0,1). We pr ...
To assess the number of life-bearing worlds in astrophysical environments, it is necessary to take the intertwined processes of abiogenesis (birth), extinction (death), and transfer of life (migration) into account. We construct a mathematical model that i ...
Nanoparticles and method for producing uniform silicate-based nanoparticles are disclosed. The method comprises a step of injecting into tubular branched elements comprising static mixers a first aqueous solution comprising a water-soluble silicate compoun ...
The present study defines a procedure for gaining a better understanding of the interaction between the aged and the virgin binders and what actually occurs during a mix process. Indeed, the authors propose a methodology to determine and quantify the clust ...
Byzantine machine learning (ML) aims to ensure the resilience of distributed learning algorithms to misbehaving (or Byzantine) machines. Although this problem received significant attention, prior works often assume the data held by the machines to be homo ...
The massive deployment of distributed acquisition and signal processing systems, as well as the ubiquity of connected devices, is currently contributing to the development of graph signal processing. Nevertheless, this discipline still suffers from the lac ...
