等效耦合和总变分的强对偶原理

IF 1.3 3区 数学 Q2 STATISTICS & PROBABILITY Electronic Journal of Probability Pub Date : 2023-01-01 DOI:10.1214/23-ejp1016
Adam Quinn Jaffe
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引用次数: 2

摘要

针对概率论中常见的两类优化问题,引入并研究了对偶性的概念。即,在抽象可测空间(Ω,F)上,我们考虑(E,G)对,其中E是Ω上的等价关系,G是F的子-σ-代数;我们说(E,G)满足“强对偶性”,如果E是(F⊗F)可测的,并且对于(Ω,F)上的所有概率测度P,P ',我们有maxA∈G|P(A)−P ' (A)|=minP≈∈Π(P,P ')(1−P≈(E)),其中Π(P,P ')表示P和P '的耦合空间,其中“max”和“min”断言实际上达到了上限值和下限值。本文的结果给出了强对偶存在的广泛充分条件,从而将Kantorovich对偶的一种形式推广到一类从拓扑学角度看是不规则的但从描述集论角度看是正则的代价函数。给定条件恢复或加强经典结果,并在随机微积分,点过程理论和随机序列模拟中产生新的结果。
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A strong duality principle for equivalence couplings and total variation
We introduce and study a notion of duality for two classes of optimization problems commonly occurring in probability theory. That is, on an abstract measurable space (Ω,F), we consider pairs (E,G) where E is an equivalence relation on Ω and G is a sub-σ-algebra of F; we say that (E,G) satisfies “strong duality” if E is (F⊗F)-measurable and if for all probability measures P,P′ on (Ω,F) we have maxA∈G|P(A)−P′(A)|=minP˜∈Π(P,P′)(1−P˜(E)), where Π(P,P′) denotes the space of couplings of P and P′, and where “max” and “min” assert that the supremum and infimum are in fact achieved. The results herein give wide sufficient conditions for strong duality to hold, thereby extending a form of Kantorovich duality to a class of cost functions which are irregular from the point of view of topology but regular from the point of view of descriptive set theory. The given conditions recover or strengthen classical results, and they have novel consequences in stochastic calculus, point process theory, and random sequence simulation.
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来源期刊
Electronic Journal of Probability
Electronic Journal of Probability 数学-统计学与概率论
CiteScore
1.80
自引率
7.10%
发文量
119
审稿时长
4-8 weeks
期刊介绍: The Electronic Journal of Probability publishes full-size research articles in probability theory. The Electronic Communications in Probability (ECP), a sister journal of EJP, publishes short notes and research announcements in probability theory. Both ECP and EJP are official journals of the Institute of Mathematical Statistics and the Bernoulli society.
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