Papers › Algorithms for Euclidean-regularised Optimal Transport
Algorithms for Euclidean-regularised Optimal Transport
Dmitry A. Pasechnyuk, Michael Persiianov, Pavel Dvurechensky, Alexander Gasnikov
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This paper addresses the Optimal Transport problem, which is regularized by the square of Euclidean ℓ₂-norm. It offers theoretical guarantees regarding the iteration complexities of the Sinkhorn--Knopp algorithm, Accelerated Gradient Descent, Accelerated Alternating Minimisation, and Coordinate Linear Variance Reduction algorithms. Furthermore, the paper compares the practical efficiency of these methods and their counterparts when applied to the entropy-regularized Optimal Transport problem. This comparison is conducted through numerical experiments carried out on the MNIST dataset.
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