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

Incentive Schemes for Participatory Sensing

We consider a participatory sensing scenario where a group of private sensors observes the same phenomenon, such as air pollution. Since sensors need to be installed and maintained, owners of sensors are inclined to provide inaccurate or random data. We de ...

2015

Lyapunov exponents of random walks in small random potential: the upper bound

Thomas Mountford, Jean-Christophe Mourrat

We consider the simple random walk on Z(d) evolving in a random i.i.d. potential taking values in [0, +infinity). The potential is not assumed integrable, and can be rescaled by a multiplicative factor lambda > 0. Completing the work started in a companion ...

Univ Washington, Dept Mathematics2015

MATHICSE Technical Report : On 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 ...

MATHICSE2014

MATHICSE Technical Report : Optimization of mesh hierarchies in multilevel Monte Carlo samplers

Fabio Nobile, Erik Gustaf Bogislaw Von Schwerin

We perform a general optimization of the parameters in the Multilevel Monte Carlo (MLMC) discretization hierarchy based on uniform discretization methods with general approximation orders and computational costs. Moreover, we discuss extensions to non-unif ...

MATHICSE2014

Convergence of quasi-optimal Stochastic Galerkin methods for a class of PDES with random coefficients

Fabio Nobile, Lorenzo Tamellini

In this work we consider quasi-optimal versions of the Stochastic Galerkin method for solving linear elliptic PDEs with stochastic coefficients. In particular, we consider the case of a finite number

N

of random inputs and an analytic dependence of the s ...

2014

Accurate and efficient evaluation of failure probability for partial different equations with random input data

Alfio Quarteroni, Peng Chen

Several computational challenges arise when evaluating the failure probability of a given system in the context of risk prediction or reliability analysis. When the dimension of the uncertainties becomes high, well established direct numerical methods can ...

Elsevier Science Sa2013

A Weighted Reduced Basis Method For Elliptic Partial Differential Equations With Random Input Data

Alfio Quarteroni, Gianluigi Rozza, Peng Chen

In this work we propose and analyze a weighted reduced basis method to solve elliptic partial differential equations (PDEs) with random input data. The PDEs are first transformed into a weighted parametric elliptic problem depending on a finite number of p ...

Siam Publications2013

Masking vs. Multiparty Computation: How Large Is the Gap for AES?

Sebastian Faust

In this paper, we evaluate the performances of state-of-the art higher-order masking schemes for the AES. Doing so, we pay a particular attention to the comparison between specialized solutions introduced exclusively as countermeasures against side-channel ...

2013

Towards a High-Speed Quantum Random Number Generator

Edoardo Charbon, Francesco Regazzoni, Samuel Burri

Randomness is of fundamental importance in various fields, such as cryptography, numerical simulations, or the gaming industry. Quantum physics, which is fundamentally probabilistic, is the best option for a physical random number generator. In this articl ...

2013

Approaches to Conditional Risk

Damir Filipovic

We present and compare two different approaches to conditional risk measures. One approach draws from convex analysis in vector spaces and presents risk measures as functions on Lp spaces, while the other approach utilizes module-based convex analysis wher ...

2012

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

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Incentive Schemes for Participatory Sensing

Lyapunov exponents of random walks in small random potential: the upper bound

MATHICSE Technical Report : On the dynamically orthogonal approximation of time dependent random PDEs

MATHICSE Technical Report : Optimization of mesh hierarchies in multilevel Monte Carlo samplers

Convergence of quasi-optimal Stochastic Galerkin methods for a class of PDES with random coefficients

Accurate and efficient evaluation of failure probability for partial different equations with random input data

A Weighted Reduced Basis Method For Elliptic Partial Differential Equations With Random Input Data

Masking vs. Multiparty Computation: How Large Is the Gap for AES?

Towards a High-Speed Quantum Random Number Generator

Approaches to Conditional Risk

Approaches to Conditional Risk

Lyapunov exponents of random walks in small random potential: the upper bound

A Weighted Reduced Basis Method For Elliptic Partial Differential Equations With Random Input Data

Accurate and efficient evaluation of failure probability for partial different equations with random input data

MATHICSE Technical Report : Optimization of mesh hierarchies in multilevel Monte Carlo samplers

Masking vs. Multiparty Computation: How Large Is the Gap for AES?

Convergence of quasi-optimal Stochastic Galerkin methods for a class of PDES with random coefficients

Incentive Schemes for Participatory Sensing

MATHICSE Technical Report : On the dynamically orthogonal approximation of time dependent random PDEs

Towards a High-Speed Quantum Random Number Generator