In Optimal Transport (OT) on a finite metric space, one defines a distance on the probability simplex that extends the distance on the ground space. The distance is the value of a Linear Programming (LP) problem on the set of non-negative-valued 2-way tables with assigned probability functions as margins. We apply to this case the methodology of moves from Algebraic Statistics (AS) and use it to derive a Monte Carlo Markov Chain (MCMC) solution algorithm.
翻译:在有限度空间的最佳运输(OT)中,您可以定义延长地面空间距离的概率简单x的距离。距离是一组非负值双向表的线性编程(LP)问题的价值,该表的概率功能被分配为边距。我们在此案中采用从代数统计(AS)移动的方法,并用它来得出蒙特卡洛·马尔科夫链(MCMC)解算法。