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Multi-index stochastic collocation convergence rates for random PDEs with parametric regularity

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Sur quelques équations aux dérivées partielles en lien avec le lemme de Poincaré

David Valentin Strütt

In this thesis, we study two distinct problems. The first problem consists of studying the linear system of partial differential equations which consists of taking a k-form, and applying the exterior derivative 'd' to it and add the wedge product with a 1- ...

EPFL2018

PDE-constrained optimal control problems with uncertain parameters using SAGA

Fabio Nobile, Matthieu Claude Martin

We consider an optimal control problem for an elliptic partial differential equation (PDE) with random coefficients. The control function is a deterministic, distributed forcing term that minimizes an expected quadratic regularized loss functional. We cons ...

2018

The analysis in Part I [1] revealed interesting properties for subgradient learning algorithms in the context of stochastic optimization. These algorithms are used when the risk functions are non-smooth or involve non-differentiable components. They have b ...

Elsevier2018

Convergence analysis of Padé approximations for Helmholtz frequency response problems

Fabio Nobile, Francesca Bonizzoni

The present work concerns the approximation of the solution map

S

associated to the parametric Helmholtz boundary value problem, i.e., the map which associates to each (real) wavenumber belonging to a given interval of interest the corresponding solution ...

2018

, ,

Several useful variance-reduced stochastic gradient algorithms, such as SVRG, SAGA, Finito, and SAG, have been proposed to minimize empirical risks with linear convergence properties to the exact minimizers. The existing convergence results assume uniform ...

IEEE2018

From Wallis to Ramanujan, in companionship with RW Gosper

Manuel Ojanguren

Accelerating the convergence of some hypergeometric series with Gosper's method leads, in a most elementary way, to some series discovered by Ramanujan, Bauer and Dougall. In particular, it is shown that one of them can be traced back to the well-known for ...

2018

Linear matrix equations, such as the Sylvester and Lyapunov equations, play an important role in various applications, including the stability analysis and dimensionality reduction of linear dynamical control systems and the solution of partial differentia ...

MATHICSE2017

Generalized linear models, where a random vector x is observed through a noisy, possibly nonlinear, function of a linear transform z = A x, arise in a range of applications in nonlinear filtering and regression. Approximate message passing (AMP) methods, b ...

IEEE2017

, ,

Part I of this work developed the exact diffusion algorithm to remove the bias that is characteristic of distributed solutions for deterministic optimization problems. The algorithm was shown to be applicable to a larger set of combination policies than ea ...

2017

Solving the Infinite-horizon Constrained LQR Problem using Accelerated Dual Proximal Methods

Colin Neil Jones, Milan Korda, Georgios Stathopoulos

This work presents an algorithmic scheme for solving the infinite-time constrained linear quadratic regulation problem. We employ an accelerated version of a popular proximal gradient scheme, commonly known as the Forward-Backward Splitting (FBS), and prov ...

Institute of Electrical and Electronics Engineers2017

Convergence analysis of Padé approximations for Helmholtz frequency response problems

Fabio Nobile, Francesca Bonizzoni

The present work concerns the approximation of the solution map

S

associated to the parametric Helmholtz boundary value problem, i.e., the map which associates to each (real) wavenumber belonging to a given interval of interest the corresponding solution ...

2018