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We present a novel distributionally robust framework for dynamic programming that uses kernel methods to design feedback control policies. Specifically, we leverage kernel mean embedding to map the transition probabilities governing the…

Systems and Control · Electrical Eng. & Systems 2023-12-20 Licio Romao , Ashish R. Hota , Alessandro Abate

We investigate a McKean-Vlasov stochastic differential equation with an additive common noise and in which the interaction is through the conditional expectation. We show that, in the presence of an additive individual noise, existence and…

Probability · Mathematics 2026-05-13 Pierre Cardaliaguet , Benjamin Jourdain

We investigate the dynamics of dissipative systems with stochastic forcing and focus in particular on mean-square stability. First we show, under a natural condition on the drift and diffusion, that the stochastic system is mean-square…

Probability · Mathematics 2026-05-01 C. Kelly , G. J. Lord , M. Ptashnyk , S. Sonner

As an enhanced version of existing results on Kac's propagation of chaos, which describes the convergence of mean-field particle systems to a system of independent McKean-Vlasov particles as the number of particles tends to infinity, we…

Probability · Mathematics 2026-05-12 Xiao-Yu Zhao

Distributed stochastic optimization intertwines (i) stochastic gradient noise, (ii) communication compression, and (iii) adaptive/normalized updates. While each factor has been studied in isolation, their joint effect under realistic…

We show well-posedness for McKean--Vlasov equations with rough common noise and progressively measurable coefficients. Our results are valid under natural regularity assumptions on the coefficients, in agreement with the respective…

Probability · Mathematics 2025-07-18 Peter K. Friz , Antoine Hocquet , Khoa Lê

We study a fully-coupled system of conditional slow-fast McKean-Vlasov Stochastic Differential Equations that exhibit full dependence on both the slow and fast components, as well as on the conditional law of the slow component. Our aim is…

Probability · Mathematics 2023-08-14 Antonios Zitridis

Topological data analysis offers a rich source of valuable information to study vision problems. Yet, so far we lack a theoretically sound connection to popular kernel-based learning techniques, such as kernel SVMs or kernel PCA. In this…

Machine Learning · Statistics 2014-12-24 Jan Reininghaus , Stefan Huber , Ulrich Bauer , Roland Kwitt

Complex models are often used to understand interactions and drivers of human-induced and/or natural phenomena. It is worth identifying the input variables that drive the model output(s) in a given domain and/or govern specific model…

Methodology · Statistics 2023-11-07 Matieyendou Lamboni

In this paper, we aim to study the asymptotic behavior for multi-scale McKean-Vlasov stochastic dynamical systems. Firstly, we obtain a central limit type theorem, i.e, the deviation between the slow component $X^{\varepsilon}$ and the…

Probability · Mathematics 2023-06-02 Wei Hong , Shihu Li , Wei Liu , Xiaobin Sun

Dense suspensions of particles dispersed in liquids are central to industrial and geophysical processes and serve as model systems for out-of-equilibrium soft matter. At high particle concentrations, they exhibit stress-dependent rheology,…

Soft Condensed Matter · Physics 2026-03-16 Orhun Ayar , Bhargav Sriram Siddani , Ishan Srivastava , Abhinendra Singh

Mean-field games with common noise provide a powerful framework for modeling the collective behavior of large populations subject to shared randomness, such as systemic risk in finance or environmental shocks in economics. These problems…

Optimization and Control · Mathematics 2025-11-13 Ruimeng Hu , Botao Jin , Mathieu Laurière , Jiacheng Zhang

In this paper, we study the stability of solutions of stochastic McKean-Vlasov equations (SMVEs) via feedback control based on discrete-time state observation. By using a specific Lyapunov function, the $H_{\infty}$ stability, asymptotic…

Probability · Mathematics 2021-10-25 Hao Wu , Junhao Hu , Shuaibin Gao , Chenggui Yuan

Numerical and analytical methods are developed for the investigation of contact sets in electrostatic-elastic deflections modeling micro-electro mechanical systems. The model for the membrane deflection is a fourth-order semi-linear partial…

Numerical Analysis · Mathematics 2020-04-20 Kelsey L. DiPietro , Ronald D. Haynes , Weizhang Huang , Alan E. Lindsay , Yufei Yu

The linear dispersion relation for collisionless kinetic tearing instabilities is calculated for a Harris equilibrium. In contrast to the conventional 2D geometry, which considers only modes at the center of the current sheet, modes can…

Plasma Physics · Physics 2018-03-14 Scott D. Baalrud , Amitava Bhattacharjee , William Daughton

We consider a discrete-time system of n coupled random vectors, a.k.a. interacting particles. The dynamics involve a vanishing step size, some random centered perturbations, and a mean vector field which induces the coupling between the…

Probability · Mathematics 2025-06-09 Pascal Bianchi , Walid Hachem , Victor Priser

In this work, we present a general Milstein-type scheme for McKean-Vlasov stochastic differential equations (SDEs) driven by Brownian motion and Poisson random measure and the associated system of interacting particles where drift,…

Probability · Mathematics 2025-01-08 Sani Biswas , Chaman Kumar , Christoph Reisinger , Verena Schwarz

A McKean-Vlasov stochastic differential equation subject to killing associated to a regularised non-conservative and path-dependent nonlinear parabolic partial differential equation is studied. The existence and pathwise uniqueness of a…

Probability · Mathematics 2025-08-01 Daniela Morale , Leonardo Tarquini , Stefania Ugolini

In this paper, we study the entrance measures of time-inhomogeneous McKean-Vlasov SDEs. The existence is obtained in great generality, where the system can be expanding globally and/or degenerate for numerous number of time intervals. When…

Probability · Mathematics 2026-04-22 Chunrong Feng , Baoyou Qu , Huaizhong Zhao

Recently in [M. Hairer, M. Hutzenthaler, and A. Jentzen, Ann. Probab. 43, 2 (2015), 468--527] and [A. Jentzen, T. M\"uller-Gronbach, and L. Yaroslavtseva, Commun. Math. Sci. 14, 6 (2016), 1477--1500] stochastic differential equations (SDEs)…

Probability · Mathematics 2021-10-12 Arnulf Jentzen , Benno Kuckuck , Thomas Müller-Gronbach , Larisa Yaroslavtseva
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