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arXiv · 2601.17196

Accelerated Sinkhorn Algorithms for Partial Optimal Transport

Nghia Thu Truong·Qui Phu Pham·Quang Nguyen·Dung Luong·Mai Tran
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Abstract

Partial Optimal Transport (POT) addresses the problem of transporting only a fraction of the total mass between two distributions, making it suitable when marginals have unequal size or contain outliers. While Sinkhorn-based methods are widely used, their complexity bounds for POT remain suboptimal and can limit scalability. We introduce Accelerated Sinkhorn for POT (ASPOT), which integrates alternating minimization with Nesterov-style acceleration in the POT setting, yielding a complexity of $\mathcal{O}(n^{7/3}\varepsilon^{-5/3})$. We also show that an informed choice of the entropic parameter $\gamma$ improves rates for the classical Sinkhorn method. Experiments on real-world applications validate our theories and demonstrate the favorable performance of our proposed methods.

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Nghia Thu Truong, Qui Phu Pham, Quang Nguyen, Dung Luong, Mai Tran. 2026-01-23. Accelerated Sinkhorn Algorithms for Partial Optimal Transport. https://arxiv.org/abs/2601.17196

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