arXiv Machine Learning August 14, 2026 By Han Dong, Jiaming Li, Yongqiang Gong, Ruixi Li, Yin Liu

Sinkhorn Linearization and the Spectral Proxy: Unifying the Statistical and Algorithmic Theory of Feature-Parameterized Inverse Optimal Transport via a Single Spectral Sandwich

Read the original on arXiv Machine Learning →

arXiv:2608. 13201v1 Announce Type: cross Abstract: We develop the statistical and algorithmic theory of inverse optimal transport (IOT) under the feature-parameterized cost C_theta(i,j) = -theta^T phi(i,j).

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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