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相关论文: Entropy-Cost Inequalities for McKean-Vlasov SDEs w…

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In many problems in data mining and machine learning, data items that need to be clustered or classified are not points in a high-dimensional space, but are distributions (points on a high dimensional simplex). For distributions, natural…

数据结构与算法 · 计算机科学 2007-07-13 Sudipto Guha , Andrew McGregor , Suresh Venkatasubramanian

This brief note aims to introduce the recent paradigm of distributional robustness in the field of shape and topology optimization. Acknowledging that the probability law of uncertain physical data is rarely known beyond a rough…

最优化与控制 · 数学 2023-01-13 Charles Dapogny , Franck Iutzeler , Andrea Meda , Boris Thibert

We study the convergence of an $N$-particle Markovian controlled system to the solution of a family of stochastic McKean-Vlasov control problems, either with a finite horizon or Schr\"odinger type cost functional. Specifically, under…

概率论 · 数学 2024-05-22 Francesco C. De Vecchi , Chiara Rigoni

In this work, we establish the existence and uniqueness of solutions to McKean-Vlasov stochastic differential equations (SDEs) driven by L\'evy processes with common noise on an infinite time horizon, by means of a contraction mapping…

概率论 · 数学 2025-11-18 Ke Xu , Fen-Fen Yang , Chenggui Yuan

For a complete connected Riemannian manifold $M$ let $V\in C^2(M)$ be such that $\mu(d x)={\rm e}^{-V(x)} \mbox{vol}(d x)$ is a probability measure on $M$. Taking $\mu$ as reference measure, we derive inequalities for probability measures…

微分几何 · 数学 2022-10-19 Li-Juan Cheng , Feng-Yu Wang , Anton Thalmaier

The maximum entropy principle is a powerful tool for solving underdetermined inverse problems. This paper considers the problem of discretizing a continuous distribution, which arises in various applied fields. We obtain the approximating…

数值分析 · 数学 2020-08-05 Ken'ichiro Tanaka , Alexis Akira Toda

We develop a unified PDE-probabilistic framework for pointwise gradient and Hessian estimates of Markov semigroups associated with stochastic differential equations with singular and unbounded coefficients. Under mild local structural…

概率论 · 数学 2026-04-02 Pengcheng Xia , Longjie Xie , Xicheng Zhang

In this article we study generalization of the classical Talagrand transport-entropy inequality in which the Wasserstein distance is replaced by the entropic transportation cost. This class of inequalities has been introduced in the recent…

概率论 · 数学 2019-07-02 Giovanni Conforti , Luigia Ripani

The mean field limits of systems of interacting diffusions (also called stochastic interacting particle systems (SIPS)) have been intensively studied since McKean \cite{mckean1966class}. The interacting diffusions pave a way to…

概率论 · 数学 2021-04-06 Lukasz Szpruch , Shuren Tan , Alvin Tse

We study stability of optimizers and convergence of Sinkhorn's algorithm for the entropic optimal transport problem. In the special case of the quadratic cost, our stability bounds imply that if one of the two entropic potentials is…

概率论 · 数学 2025-10-06 Alberto Chiarini , Giovanni Conforti , Giacomo Greco , Luca Tamanini

In this paper we consider a mean-field stochastic differential equation, also called Mc Kean-Vlasov equation, with initial data $(t,x)\in[0,T]\times R^d,$ which coefficients depend on both the solution $X^{t,x}_s$ but also its law. By…

概率论 · 数学 2014-07-07 Rainer Buckdahn , Juan Li , Shige Peng , Catherine Rainer

Mixture distributions are extensively used as a modeling tool in diverse areas from machine learning to communications engineering to physics, and obtaining bounds on the entropy of probability distributions is of fundamental importance in…

信息论 · 计算机科学 2022-12-05 James Melbourne , Saurav Talukdar , Shreyas Bhaban , Mokshay Madiman , Murti V. Salapaka

We consider a probabilistic formulation of a singular two-phase Stefan problem in one space dimension, which amounts to a coupled system of two McKean-Vlasov stochastic differential equations. In the financial context of systemic risk, this…

概率论 · 数学 2023-04-27 Graeme Baker , Mykhaylo Shkolnikov

In this work we extend the framework of monotone dynamical systems to a broad and important class of stochastic equations, namely cooperative McKean-Vlasov SDEs with multiplicative noise. Under a locally dissipative assumption, our main…

概率论 · 数学 2026-01-06 Chunlin Liu , Baoyou Qu , Jinxiang Yao , Yanpeng Zhi

We formulate a trajectorial version of the relative entropy dissipation identity for McKean$-$Vlasov diffusions, extending the results of the papers [FJ16,KST20a], which apply to non-interacting diffusions. Our stochastic analysis approach…

概率论 · 数学 2021-05-27 Bertram Tschiderer , Lane Chun Yeung

In contrast to ordinary stochastic differential equations (SDEs), the numerical simulation of McKean-Vlasov stochastic differential equations (MV-SDEs) requires approximating the distribution law first. Based on the theory of propagation of…

数值分析 · 数学 2025-06-12 Yuhang Zhang , Minghui Song

In recent years, remarkable progress has been made for Distribution dependent stochastic equations (DDSDEs) with singular interactions, existing results include wellposedness, propagation of chaos, entropy cost inequality and ergodicity. As…

概率论 · 数学 2026-04-13 Panpan Ren

By refining a recent result of Xie and Zhang, we prove the exponential ergodicity under a weighted variation norm for singular SDEs with drift containing a local integrable term and a coercive term. This result is then extended to singular…

概率论 · 数学 2023-03-10 Feng-Yu Wang

We study a numerical method to compute probability density functions of solutions of stochastic differential equations. The method is sometimes called the numerical path integration method and has been shown to be fast and accurate in…

动力系统 · 数学 2016-11-29 Linghua Chen , Espen Robstad Jakobsen , Arvid Naess

We consider a system of $N$ interacting particles, governed by transport and diffusion, that converges in a mean-field limit to the solution of a McKean-Vlasov equation. From the observation of a trajectory of the system over a fixed time…

统计理论 · 数学 2021-03-16 Laetitia Della Maestra , Marc Hoffmann