Publication

Asymptotic symmetry and asymptotic solutions to Ito stochastic differential equations

Publications associées (23)

A Combination Technique for Optimal Control Problems Constrained by Random PDEs

We present a combination technique based on mixed differences of both spatial approximations and quadrature formulae for the stochastic variables to solve efficiently a class of optimal control problems (OCPs) constrained by random partial differential equ ...

2024

Nonparametric estimation for SDE with sparsely sampled paths: An FDA perspective

Victor Panaretos, Neda Mohammadi Jouzdani

We consider the problem of nonparametric estimation of the drift and diffusion coefficients of a Stochastic Differential Equation (SDE), based on n independent replicates {Xi(t) : t is an element of [0 , 1]}13 d B(t), where alpha is an element of {0 , 1} a ...

Elsevier2024

On the asymptotic behavior of solutions to the Vlasov-Poisson system

Klaus Martin Widmayer

We prove small data modified scattering for the Vlasov-Poisson system in dimension

d=3

using a method inspired from dispersive analysis. In particular, we identify a simple asymptotic dynamic related to the scattering mass. ...

2022

The Error-Feedback Framework: Better Rates for SGD with Delayed Gradients and Compressed Updates

Sai Praneeth Reddy Karimireddy, Sebastian Urban Stich

We analyze (stochastic) gradient descent (SGD) with delayed updates on smooth quasi-convex and non-convex functions and derive concise, non-asymptotic, convergence rates. We show that the rate of convergence in all cases consists of two terms: (i) a stocha ...

Microtome Publishing2020

An overview of a new sensor calibration platform

Jan Skaloud, Stéphane Guerrier, Philipp Clausen

Inertial sensors are increasingly being employed in different types of applications. The reduced cost and the extremely small size makes them the number-one-choice in miniature embedded devices like phones, watches, and small unmanned aerial vehicles. The ...

2017

Gaussian versus Sparse Stochastic Processes : Construction, Regularity, Compressibility

Julien René Pierre Fageot

Although our work lies in the field of random processes, this thesis was originally motivated by signal processing applications, mainly the stochastic modeling of sparse signals. We develop a mathematical study of the innovation model, under which a signal ...

EPFL2017

A Combination Technique for Optimal Control Problems Constrained by Random PDEs

Fabio Nobile, Tommaso Vanzan

2024

Nonparametric estimation for SDE with sparsely sampled paths: An FDA perspective

Victor Panaretos, Neda Mohammadi Jouzdani

Elsevier2024

On the asymptotic behavior of solutions to the Vlasov-Poisson system

Klaus Martin Widmayer

We prove small data modified scattering for the Vlasov-Poisson system in dimension

d=3

using a method inspired from dispersive analysis. In particular, we identify a simple asymptotic dynamic related to the scattering mass. ...

2022

The Error-Feedback Framework: Better Rates for SGD with Delayed Gradients and Compressed Updates

Sai Praneeth Reddy Karimireddy, Sebastian Urban Stich

Microtome Publishing2020

An overview of a new sensor calibration platform

Jan Skaloud, Stéphane Guerrier, Philipp Clausen

2017

Generalized Pickands constants and stationary max-stable processes

Sebastian Engelke

Pickands constants play a crucial role in the asymptotic theory of Gaussian processes. They are commonly defined as the limits of a sequence of expectations involving fractional Brownian motions and, as such, their exact value is often unknown. Recently, D ...

Springer Verlag2017

Gaussian versus Sparse Stochastic Processes : Construction, Regularity, Compressibility

Julien René Pierre Fageot

EPFL2017

Stochastic partial differential equations driven by Lévy white noises : generalized random processes, random field solutions and regularity

Thomas Marie Jean-Baptiste Humeau

We study various aspects of stochastic partial differential equations driven by Lévy white noise. This driving noise, which is a generalization of Gaussian white noise, can be viewed either as a generalized random process or as an independently scattered r ...

EPFL2017

Stabilized Numerical Methods for Stochastic Differential Equations driven by Diffusion and Jump-Diffusion Processes

Adrian Blumenthal

Stochastic models that account for sudden, unforeseeable events play a crucial role in many different fields such as finance, economics, biology, chemistry, physics and so on. That kind of stochastic problems can be modeled by stochastic differential equat ...

EPFL2015

On the Connection between the Hamilton-Jacobi-Bellman and the Fokker-Planck Control Frameworks

Fabio Nobile

In the framework of stochastic processes, the connection between the dynamic programming scheme given by the Hamilton-Jacobi-Bellman equation and a recently proposed control approach based on the Fokker-Planck equation is discussed. Under appropriate assum ...

2014