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Brown-Resnick processes are max-stable processes that are associated to Gaussian processes. Their simulation is often based on the corresponding spectral representation which is not unique. We study to what extent simulation accuracy and…

Probability · Mathematics 2018-10-17 Marco Oesting , Kirstin Strokorb

We derive novel algorithms for optimization problems constrained by partial differential equations describing multiscale particle dynamics, including non-local integral terms representing interactions between particles. In particular, we…

Numerical Analysis · Mathematics 2021-09-09 Mildred Aduamoah , Benjamin D. Goddard , John W. Pearson , Jonna C. Roden

We consider the problem of tracking a target whose dynamics is modeled by a continuous It\=o semi-martingale. The aim is to minimize both deviation from the target and tracking efforts. We establish the existence of asymptotic lower bounds…

Probability · Mathematics 2015-10-16 Jiatu Cai , Mathieu Rosenbaum , Peter Tankov

The natural analogue for a Levy process of Cramer's estimate for a reflected random walk is a statement about the exponential rate of decay of the tail of the characteristic measure of the height of an excursion above the minimum. We…

Probability · Mathematics 2007-05-23 R. A. Doney , R. A. Maller

We prove simple general formulas for expectations of functions of a L\'evy process and its running extremum. Under additional conditions, we derive analytical formulas using the Fourier/Laplace inversion and Wiener-Hopf factorization, and…

Probability · Mathematics 2023-08-01 Svetlana Boyarchenko , Sergei Levendorskiĭ

We study the problem of empirical minimization for variance-type functionals over functional classes. Sharp non-asymptotic bounds for the excess variance are derived under mild conditions. In particular, it is shown that under some…

Numerical Analysis · Mathematics 2021-08-03 D. Belomestny , L. Iosipoi , Q. Paris , N. Zhivotovskiy

Many problems in computational science and engineering are simultaneously characterized by the following challenging issues: uncertainty, nonlinearity, nonstationarity and high dimensionality. Existing numerical techniques for such models…

Numerical Analysis · Mathematics 2017-03-20 Peter Benner , Sergey Dolgov , Akwum Onwunta , Martin Stoll

Existing implementations of gradient-based optimisation methods typically assume that the problem is posed in Euclidean space. When solving optimality problems on function spaces, the functional derivative is then inaccurately represented…

Optimization and Control · Mathematics 2016-06-28 Tobias Schwedes , Simon W. Funke , David A. Ham

The optimal stopping problem for a Hunt processes on $\R$ is considered via the representation theory of excessive functions. In particular, we focus on infinite horizon (or perpetual) problems with one-sided structure, that is, there…

Probability · Mathematics 2007-05-23 Ernesto Mordecki , Paavo Salminen

Bounds on the log partition function are important in a variety of contexts, including approximate inference, model fitting, decision theory, and large deviations analysis. We introduce a new class of upper bounds on the log partition…

Machine Learning · Computer Science 2013-01-07 Martin Wainwright , Tommi S. Jaakkola , Alan Willsky

We derive characteristic function identities for conditional distributions of an r-trimmed Levy process given its r largest jumps up to a designated time t. Assuming the underlying Levy process is in the domain of attraction of a stable…

Probability · Mathematics 2018-09-06 Yuguang F. Ipsen , Peter Kevei , Ross A. Maller

In this article we consider shape optimization problems as optimal control problems via the method of mappings. Instead of optimizing over a set of admissible shapes a reference domain is introduced and it is optimized over a set of…

Optimization and Control · Mathematics 2021-06-09 Johannes Haubner , Martin Siebenborn , Michael Ulbrich

This paper considers an optimal impulse control problem of dynamical systems generated by a flow. The performance criteria are total costs over the infinite time horizon. Apart from the main performance to be minimized, there are multiple…

Optimization and Control · Mathematics 2020-10-27 Alexey Piunovskiy , Yi Zhang

Several versions of It\^{o}'s formula have been obtained in the context of the functional stochastic calculus. Here, we revisit this topic in two ways. First, by defining a notion of derivative along a functional, we extend the setting of…

Probability · Mathematics 2022-02-25 Christian Houdré , Jorge Víquez

Variational problems of splitting-type with mixed linear-superlinear growth conditions are considered. In the twodimensional case the minimizing problem is given by \[ J [w] = \int_{\Omega} \Big[f_1\big(\partial_1 w\big) +…

Analysis of PDEs · Mathematics 2020-07-30 Michael Bildhauer , Martin Fuchs

In this paper we study a representation problem first considered in a simpler version by Bank and El Karoui [2004]. A key ingredient to this problem is a random measure $\mu$ on the time axis which in the present paper is allowed to have…

Probability · Mathematics 2018-10-22 Peter Bank , David Besslich

This paper studies approximate solutions of a linear fractional vector optimization problem without requiring boundedness of the constraint set. We establish necessary and sufficient conditions for approximating weakly efficient points of…

Optimization and Control · Mathematics 2024-12-12 Nguyen Thi Thu Huong

We consider branching Brownian motion on the real line with the following selection mechanism: Every time the number of particles exceeds a (large) given number $N$, only the $N$ right-most particles are kept and the others killed. After…

Probability · Mathematics 2018-06-20 Pascal Maillard

The concept of a L\'evy subordinator is generalized to a family of non-decreasing stochastic processes, which are parameterized in terms of two Bernstein functions. Whereas the independent increments property is only maintained in the…

Probability · Mathematics 2019-09-10 Jan-Frederik Mai , Matthias Scherer

Evolutionary computation offers a variety of tools to solve complex real-world optimization problems. However, research often focuses on smaller, simplified problems and optimization algorithms that sometimes miss expectations in real-world…