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Gradient-based optimisation of the conditional-value-at-risk using the multi-level Monte Carlo method

Related publications (78)

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Model Uncertainty And Scenario Aggregation

Damir Filipovic, Mathieu Jacques David Cambou

This paper provides a coherent method for scenario aggregation addressing model uncertainty. It is based on divergence minimization from a reference probability measure subject to scenario constraints. An example from regulatory practice motivates the defi ...

Wiley-Blackwell2017

Expectations-driven cycles in the housing market

Luisa Lambertini

This paper explores the transmission of "news shocks" in a model of the housing market and shows that anticipated signals or beliefs of future macroeconomic developments can generate boom-bust cycles in the housing market and lead to business cycle fluctua ...

2017

Lipschitz changes of variables between perturbations of log-concave measures

Maria Colombo

Extending a result of Caffarelli, we provide global Lipschitz changes of variables between compactly supported perturbations of log-concave measures. The result is based on a combination of ideas from optimal transportation theory and a new Pogorelov-type ...

2017

MATHICSE Technical Report : Dimensionality reduction of parameter-dependent problems through proper orthogonal decomposition

Alfio Quarteroni, Andrea Manzoni, Federico Negri

The numerical solution of partial differential equations (PDEs) depending on para- metrized or random input data is computationally intensive. Reduced order modeling techniques, such as the reduced basis methods, have been developed to alleviate this compu ...

MATHICSE2016

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In this paper we develop and analyze a multilevel weighted reduced basis method for solving stochastic optimal control problems constrained by Stokes equations. We prove the analytic regularity of the optimal solution in the probability space under certain ...

Springer Heidelberg2016

MATHICSE Technical Report : Multilevel tensor approximation of PDEs with random data

Daniel Kressner, Jonas Ballani, Michael Dieter Peters

In this paper, we introduce and analyze a new low-rank multilevel strategy for the solution of random diffusion problems. Using a standard stochastic collocation scheme, we first approximate the infinite dimensional random problem by a deterministic parame ...

MATHICSE2016

Nematodynamics and random homogenization

Tudor Ratiu

We study the homogenization problem for the system of equations of dynamics of a mixture of liquid crystals with random structure. We consider a simplified form of the Ericksen-Leslie equations for an incompressible medium with inhomogeneous density with r ...

Taylor & Francis2016

Error Analysis of the Dynamically Orthogonal Approximation of Time Dependent Random PDEs

Fabio Nobile, Eleonora Musharbash

In this work we discuss the dynamically orthogonal (DO) approximation of time dependent partial differential equations with random data. The approximate solution is expanded at each time instant on a time dependent orthonormal basis in the physical domain ...

2015

We analyze the recent Multi-index Stochastic Collocation (MISC) method for computing statistics of the solution of a partial differential equation with random data, where the random coefficient is parametrized by means of a countable sequence of terms in a ...

MATHICSE2015

Pushed by the proliferation of antennas and of multiuser scenarios, matrices with random entries are appearing more and more frequently in information theory. This leads to the study of matrix channels, where the capacity depends on the distribution of the ...

EPFL2015