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We consider a control constrained parabolic optimal control problem and use variational discretization for its time semi-discretization. The state equation is treated with a Petrov-Galerkin scheme using a piecewise constant Ansatz for the…

Optimization and Control · Mathematics 2015-03-09 Nikolaus von Daniels , Michael Hinze , Morten Vierling

We study ergodic properties of a class of Markov-modulated general birth-death processes under fast regime switching. The first set of results concerns the ergodic properties of the properly scaled joint Markov process with a parameter that…

Probability · Mathematics 2019-09-17 Ari Arapostathis , Guodong Pang , Yi Zheng

This paper focuses on the regularization of backward time-fractional diffusion problem on unbounded domain. This problem is well-known to be ill-posed, whence the need of a regularization method in order to recover stable approximate…

Numerical Analysis · Mathematics 2022-01-03 Walter Simo Tao Lee

We consider a change-point detection problem for a simple class of Piecewise Deterministic Markov Processes (PDMPs). A continuous-time PDMP is observed in discrete time and through noise, and the aim is to propose a numerical method to…

Optimization and Control · Mathematics 2017-09-28 Alice Cleynen , Benoîte de Saporta

This paper considers the temporal discretization of an inverse problem subject to a time fractional diffusion equation. Firstly, the convergence of the L1 scheme is established with an arbitrary sectorial operator of spectral angle $< \pi/2…

Numerical Analysis · Mathematics 2022-01-07 Binjie Li , Xiaoping Xie , Yubin Yan

Particle smoothing methods are used for inference of stochastic processes based on noisy observations. Typically, the estimation of the marginal posterior distribution given all observations is cumbersome and computational intensive. In…

Machine Learning · Computer Science 2017-05-24 H. -Ch. Ruiz , H. J. Kappen

This paper is concerned with the partial information optimal control problem of wa controlled forward-backward stochastic differential equation of jump diffusion with correlated noises between the system and the observation. For this type…

Probability · Mathematics 2017-08-28 Qingxin Meng

Adapting pretrained diffusion models to downstream objectives such as inverse problems often requires expensive test-time guidance or optimization. We propose a principled framework for generating high-quality reward-aligned samples at…

Machine Learning · Computer Science 2026-05-22 Kushagra Pandey , Farrin Marouf Sofian , Jan Niklas Groeneveld , Felix Draxler , Stephan Mandt

While imitation learning provides a simple and effective framework for policy learning, acquiring consistent actions during robot execution remains a challenging task. Existing approaches primarily focus on either modifying the action…

Robotics · Computer Science 2024-07-24 Xiao Liu , Fabian Weigend , Yifan Zhou , Heni Ben Amor

A singularly perturbed parabolic problem of convection-diffusion type with a discontinuous initial condition is examined. An analytic function is identified which matches the discontinuity in the initial condition and also satisfies the…

Numerical Analysis · Mathematics 2022-02-15 Jose Luis Gracia , Eugene O'Riordan

This work collects some methodological insights for numerical solution of a "minimum-dispersion" control problem for nonlinear stochastic differential equations, a particular relaxation of the covariance steering task. The main ingredient…

Optimization and Control · Mathematics 2025-10-16 Roman Chertovskih , Nikolay Pogodaev , Maxim Staritsyn , A. Pedro Aguiar

This paper studies an optimal control problem for continuous-time stochastic systems subject to reachability objectives specified in a subclass of metric interval temporal logic specifications, a temporal logic with real-time constraints.…

Systems and Control · Computer Science 2015-04-21 Jie Fu , Ufuk Topcu

This paper investigates the optimal control problem for a class of parabolic equations where the diffusion coefficient is influenced by a control function acting nonlocally. Specifically, we consider the optimization of a cost functional…

Optimization and Control · Mathematics 2025-03-11 Stefana-Lucia Anita , Luca Di Persio

We consider control-constrained linear-quadratic optimal control problems on evolving surfaces. In order to formulate well-posed problems, we prove existence and uniqueness of weak solutions for the state equation, in the sense of…

Optimization and Control · Mathematics 2015-03-19 Morten Vierling

Sequential Monte Carlo methods, also known as particle methods, are a widely used set of computational tools for inference in non-linear non-Gaussian state-space models. In many applications it may be necessary to compute the sensitivity,…

Statistics Theory · Mathematics 2011-06-14 Pierre Del Moral , Arnaud Doucet , Sumeetpal Singh

The application of deep learning for partial differential equation (PDE)-constrained control is gaining increasing attention. However, existing methods rarely consider safety requirements crucial in real-world applications. To address this…

Machine Learning · Computer Science 2025-05-19 Peiyan Hu , Xiaowei Qian , Wenhao Deng , Rui Wang , Haodong Feng , Ruiqi Feng , Tao Zhang , Long Wei , Yue Wang , Zhi-Ming Ma , Tailin Wu

We give a probabilistic interpretation of the Monte Carlo scheme proposed by Fahim, Touzi and Warin [Ann. Appl. Probab. 21 (2011) 1322-1364] for fully nonlinear parabolic PDEs, and hence generalize it to the path-dependent (or…

Probability · Mathematics 2014-07-03 Xiaolu Tan

We analyze an optimal control problem with pointwise tracking for a fractional semilinear elliptic partial differential equation. The diffusion is characterized by the spectral fractional Laplacian $(-\Delta)^s$ with $s \in (1/2,1)$, a…

Optimization and Control · Mathematics 2026-04-17 Enrique Otarola , Abner J. Salgado

There has recently been considerable interest in using a nonstandard piecewise approximation to formulate fractional order differential equations as difference equations that describe the same dynamical behaviour and are more amenable to a…

Numerical Analysis · Mathematics 2016-05-09 Christopher N Angstmann , Bruce I Henry , Anna V McGann

We study the estimation of the value function for continuous-time Markov diffusion processes using a single, discretely observed ergodic trajectory. Our work provides non-asymptotic statistical guarantees for the least-squares…

Machine Learning · Computer Science 2025-02-07 Wenlong Mou
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