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Many decision problems in economics, information technology, and industry can be transformed to an optimal stopping of adapted random vectors with some utility function over the set of Markov times with respect to filtration build by the…

Optimization and Control · Mathematics 2020-11-04 Krzysztof Szajowski

In this work, we develop a collection of novel methods for the entropic-regularised optimal transport problem, which are inspired by existing mirror descent interpretations of the Sinkhorn algorithm used for solving this problem. These are…

Optimization and Control · Mathematics 2025-07-17 Vishwak Srinivasan , Qijia Jiang

We discuss the optimal Markovian coupling before an exponential time of the Kolmogorov diffusion, and a class of related stochastic control problems in which the aim is to hit the origin before an exponential time. We provide a scaling…

Probability · Mathematics 2007-05-23 Kalvis M. Jansons , Paul D. Metcalfe

We consider the following geometric optics problem: Construct a system of two reflectors which transforms a spherical wavefront generated by a point source into a beam of parallel rays. This beam has a prescribed intensity distribution. We…

Analysis of PDEs · Mathematics 2015-05-13 Tilmann Glimm

In this paper, we derive sufficient and necessary maximum principles for a stochastic optimal control problem where the system state is given by a controlled stochastic differential equation with default. We prove existence of a unique…

Optimization and Control · Mathematics 2021-05-26 Khalida Bachir Cherif , Nacira Agram , Kristina Dahl

This paper is devoted to an optimal control problem of fully coupled forward-backward stochastic differential equations driven by sub-diffusion, whose solutions are not Markov processes. The stochastic maximum principle is obtained, where…

Optimization and Control · Mathematics 2025-03-11 Chenhui Hao , Jingtao Shi , Shuaiqi Zhang

We solve the Skorokhod embedding problem for a class of stochastic processes satisfying an inhomogeneous stochastic differential equation (SDE) of the form $d A_t =\mu (t, A_t) d t + \sigma(t, A_t) d W_t$. We provide sufficient conditions…

Probability · Mathematics 2019-06-19 Stefan Ankirchner , Stefan Engelhardt , Alexander Fromm , Goncalo dos Reis

We show that a simple geometric result suffices to derive the form of the optimal solution in a large class of finite and infinite-dimensional maximum entropy problems concerning probability distributions, spectral densities and covariance…

Optimization and Control · Mathematics 2012-12-24 Michele Pavon , Augusto Ferrante

We investigate optimal control problems with $L^0$ constraints, which restrict the measure of the support of the controls. We prove necessary optimality conditions of Pontryagin maximum principle type. Here, a special control perturbation…

Optimization and Control · Mathematics 2022-08-04 Daniel Wachsmuth

We solve the problem of optimal stopping of a Brownian motion subject to the constraint that the stopping time's distribution is a given measure consisting of finitely-many atoms. In particular, we show that this problem can be converted to…

Optimization and Control · Mathematics 2017-07-07 Erhan Bayraktar , Christopher W. Miller

We prove a maximum principle for the problem of optimal control for a fractional diffusion with infinite horizon. Further, we show existence of fractional backward stochastic differential equations on infinite horizon. We illustrate our…

Optimization and Control · Mathematics 2012-06-29 Sven Haadem

We study an infinite horizon optimal stopping problem which arises naturally in the optimal timing of a firm/project sale or in the valuation of natural resources: the functional to be maximised is a sum of a discounted running reward and a…

Optimization and Control · Mathematics 2016-12-08 Jan Palczewski , Lukasz Stettner

In this paper, we consider multistopping problems for finite discrete time sequences $X_1,...,X_n$. $m$-stops are allowed and the aim is to maximize the expected value of the best of these $m$ stops. The random variables are neither assumed…

Probability · Mathematics 2012-01-04 Andreas Faller , Ludger Rüschendorf

We provide a framework for high-order discretizations of nonlinear scalar convection-diffusion equations that satisfy a discrete maximum principle. The resulting schemes can have arbitrarily high order accuracy in time and space, and can be…

Numerical Analysis · Mathematics 2021-09-20 Manuel Quezada de Luna , David I. Ketcheson

In this work, we investigate the optimal control problem for continuous-time Markov decision processes with the random impact of the environment. We provide conditions to show the existence of optimal controls under finite-horizon criteria.…

Optimization and Control · Mathematics 2020-06-23 Jinghai Shao , Kun Zhao

This paper develops an approach for solving perpetual discounted optimal stopping problems for multidimensional diffusions, with special emphasis on the $d$-dimensional Wiener process. We first obtain some verification theorems for…

Probability · Mathematics 2016-11-04 Sören Christensen , Fabián Crocce , Ernesto Mordecki , Paavo Salminen

The article is devoted to the problem of applying the maximum principle for finding optimal control parameters in simulation tasks of interest for a variety of engineering and industrial systems and processes. Especially important is the…

Optimization and Control · Mathematics 2018-03-28 Ivan V. Kazachkov

We study a class of singular stochastic control problems for a one-dimensional diffusion $X$ in which the performance criterion to be optimised depends explicitly on the running infimum $I$ (or supremum $S$) of the controlled process. We…

Optimization and Control · Mathematics 2025-01-30 Giorgio Ferrari , Neofytos Rodosthenous

Consider a general nonlinear optimal control problem in finite dimension, with constant state and/or control delays. By the Pontryagin Maximum Principle, any optimal trajectory is the projection of a Pontryagin extremal. We establish that,…

Optimization and Control · Mathematics 2018-11-13 Bruno Hérissé , Riccardo Bonalli , Emmanuel Trélat

The continuous dynamical system approach to deep learning is explored in order to devise alternative frameworks for training algorithms. Training is recast as a control problem and this allows us to formulate necessary optimality conditions…

Machine Learning · Computer Science 2018-06-05 Qianxiao Li , Long Chen , Cheng Tai , Weinan E
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