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We give the distribution of $M_n$, the maximum of a sequence of $n$ observations from a moving average of order 1. Solutions are first given in terms of repeated integrals and then for the case where the underlying independent random…

Methodology · Statistics 2009-09-07 Christopher S. Withers , Saralees Nadarajah

We define a class of reflected backward stochastic differential equation (RBSDE) driven by a marked point process (MPP) and a Brownian motion, where the solution is constrained to stay above a given c\`adl\`ag process. The MPP is only…

Probability · Mathematics 2017-09-28 Nahuel Foresta

The aim of this paper is to improve the large deviation principle for the number of descents in a random permutation by establishing a sharp large deviation principle of any order. We shall also prove a sharp large deviation principle of…

Probability · Mathematics 2024-07-09 Bernard Bercu , Michel Bonnefont , Luis Fredes , Adrien Richou

The main objective of this paper is to investigate the spectral properties, maximum principles, and shape optimization problems for a broad class of nonlinear ``superposition operators" defined as continuous superpositions of operators of…

Analysis of PDEs · Mathematics 2026-05-26 Yergen Aikyn , Sekhar Ghosh , Vishvesh Kumar , Michael Ruzhansky

We give a direct derivation of the distribution of the maximum and the location of the maximum of one-sided and two-sided Brownian motion with a negative parabolic drift. The argument uses a relation between integrals of special functions,…

Probability · Mathematics 2013-12-18 Piet Groeneboom , Steven Lalley , Nico Temme

We study a 1D transport equation with nonlocal velocity. First, we prove eventual regularization of the viscous regularization when dissipation is in the supercritical range with non-negative initial data. Next, we will prove global…

Analysis of PDEs · Mathematics 2013-10-24 Tam Do

The aim of this note is twofold. Firstly, we prove an abstract version of the Calder\'on transference principle for inequalities of admissible type in the general commutative multilinear and multiparameter setting. Such an operation does…

Dynamical Systems · Mathematics 2024-05-08 Dariusz Kosz

In this paper, we study the relationship between general maximum principle and dynamic programming principle for risk-sensitive stochastic optimal control problems, where the control domain is not necessarily convex. The original problem is…

Optimization and Control · Mathematics 2026-02-06 Huanqing Dong , Jingtao Shi

In this paper, we establish a strong maximum principle for fractional diffusion equations with multiple Caputo derivatives in time, and investigate a related inverse problem of practical importance. Exploiting the solution properties and…

Analysis of PDEs · Mathematics 2019-04-12 Yikan Liu

We consider Piecewise Deterministic Markov Processes (PDMPs) with a finite set of discrete states. In the regime of fast jumps between discrete states, we prove a law of large number and a large deviation principle. In the regime of fast…

Probability · Mathematics 2008-09-16 A. Faggionato , D. Gabrielli , M. Ribezzi Crivellari

A principle of maximum entropy is proposed in the context of viscous incompressible flow in Eulerian coordinates. The relative entropy functional, defined over the space of $L^2$ divergence-free velocity fields, is maximized relative to…

Fluid Dynamics · Physics 2024-02-23 Gui-Qiang G. Chen , James Glimm , Hamid Said

In this paper, we establish a general stochastic maximum principle for optimal control for systems described by a continuous-time Markov regime-switching stochastic recursive utilities model. The control domain is postulated not to be…

Optimization and Control · Mathematics 2019-05-02 Liangquan Zhang , Xun Li

In this paper we present the distribution of the maximum of the telegraph process in the cases where the initial velocity is positive or negative with an even and an odd number of velocity reversals. For the telegraph process with positive…

Probability · Mathematics 2020-03-10 Fabrizio Cinque , Enzo Orsingher

The finite state semi-Markov process is a generalization over the Markov chain in which the sojourn time distribution is any general distribution. In this article we provide a sufficient stochastic maximum principle for the optimal control…

Optimization and Control · Mathematics 2014-07-14 Amogh Deshpande

We consider the utility maximization problem under convex constraints with regard to theoretical results which allow the formulation of algorithmic solvers which make use of deep learning techniques. In particular for the case of random…

Computational Finance · Quantitative Finance 2022-02-17 Kristof Wiedermann

We study the strong maximum principle for horizontal (p-) mean curvature operator and p-(sub)laplacian operator on subriemannian manifolds including, in particular, Heisenberg groups and Heisenberg cylinders. Under a certain Hormander type…

Differential Geometry · Mathematics 2016-11-09 Jih-Hsin Cheng , Hung-Lin Chiu , Jenn-Fang Hwang , Paul Yang

Existing diffusion-based methods for inverse problems sample from the posterior using score functions and accept the generated random samples as solutions. In applications that posterior mean is preferred, we have to generate multiple…

Machine Learning · Computer Science 2024-10-10 Zhipeng Xue , Penghao Cai , Xiaojun Yuan , Xiqi Gao

In this communication, we prove some important limits of the principal eigenvalue for nonlocal operator of Neumann type with respect to the parameters, which are significant in the understanding of dynamics of biological populations. We…

Spectral Theory · Mathematics 2019-11-15 Hoang-Hung Vo

We give the distribution of $M_n$, the maximum of a sequence of $n$ observations from a moving average of order 1. Solutions are first given in terms of repeated integrals and then for the case where the underlying independent random…

Methodology · Statistics 2009-04-06 Christopher S. Withers , Saralees Nadarajah

We examine the \emph{submodular maximum coverage problem} (SMCP), which is related to a wide range of applications. We provide the first variational approximation for this problem based on the Nemhauser divergence, and show that it can be…

Machine Learning · Computer Science 2020-06-11 Jian Du , Zhigang Hua , Shuang Yang
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