Orlicz-space regularization for optimal transport and algorithms for quadratic regularization
We investigate the continuous optimal transport problem in the so-called Kantorovich form, i.e. given two Radon measures on two compact sets, we seek an optimal transport plan which is another Radon measure on the product of the sets that has these two measures as marginals and minimizes a certain cost function. We consider regularization of the problem with so-called Young's functions, which forces the optimal transport plan to be a function in the corresponding Orlicz space rather than a Radon measure. We derive the predual problem and show strong duality and existence of primal solutions to the regularized problem. Existence of (pre-)dual solutions will be shown for the special case of $L^p$ regularization for $p\geq2$. Then we derive four algorithms to solve the dual problem of the quadratically regularized problem: A cyclic projection method, a dual gradient decent, a simple fixed point method, and Nesterov's accelerated gradient, all of which have a very low cost per iteration.