5 citations · 10 across the 7 of their papers we have counts for
7 papers
Numerical approximation of the stochastic heat equation with a distributional reaction term
Ludovic Goudenège, El Mehdi Haress, Alexandre Richard
We study the numerical approximation of the stochastic heat equation with a distributional reaction term. Under a condition on the Besov regularity of the reaction term, it was pro…
Estimation of several parameters in discretely-observed Stochastic Differential Equations with additive fractional noise
El Mehdi Haress, Alexandre Richard
We investigate the problem of joint statistical estimation of several parameters for a stochastic differential equation driven by an additive fractional Brownian motion. Based on d…
Numerical approximation of SDEs with fractional noise and distributional drift
Ludovic Goudenège, El Mehdi Haress, Alexandre Richard
We study the numerical approximation of SDEs with singular drifts (including distributions) driven by a fractional Brownian motion. Under the Catellier-Gubinelli condition that imp…
Long time Hurst regularity of fractional SDEs and their ergodic means
El Mehdi Haress, Alexandre Richard
The fractional Brownian motion can be considered as a Gaussian field indexed by , where is the Hurst parameter. On compact time intervals…
Spectral risk-based learning using unbounded losses
Matthew J. Holland, El Mehdi Haress
In this work, we consider the setting of learning problems under a wide class of spectral risk (or "L-risk") functions, where a Lipschitz-continuous spectral density is used to fle…
Learning with CVaR-based feedback under potentially heavy tails
Matthew J. Holland, El Mehdi Haress
We study learning algorithms that seek to minimize the conditional value-at-risk (CVaR), when all the learner knows is that the losses incurred may be heavy-tailed. We begin by stu…
Estimation Of all parameters in the Fractional Ornstein-Uhlenbeck model under discrete observations
El Mehdi Haress, Yaozhong Hu
Let the Ornstein-Uhlenbeck process driven by a fractional Brownian motion , described by be observed at discrete time instant…