Abstract − We address the estimation of quantiles from heavy-tailed distributions when functional covariate information is available and in the case where the order of the quanti...
Abstract-- We introduce an extension of the notion of homogeneous approximation to make it valid both at the origin and at infinity (homogeneity in the bi-limit). Exploiting this e...
Vincent Andrieu, Laurent Praly, Alessandro Astolfi
We consider a multi-agent optimization problem where agents aim to cooperatively minimize a sum of local objective functions subject to a global inequality constraint and a global ...
We consider the homogenization of parabolic equations with large spatiallydependent potentials modeled as Gaussian random fields. We derive the homogenized equations in the limit ...
Abstract--Recurrent neural networks have become a prominent tool for optimizations including linear or nonlinear variational inequalities and programming, due to its regular mathem...