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Decreasing Entropic Regularization Averaged Gradient for Semi-Discrete Optimal Transport

arXiv — stat.ML•Monday, November 3, 2025 at 5:00:00 AM
NeutralArtificial Intelligence

Decreasing Entropic Regularization Averaged Gradient for Semi-Discrete Optimal Transport

A new paper on arXiv discusses a method for improving Optimal Transport (OT) problems by adaptively decreasing entropic regularization as solutions are approached. This approach aims to reduce bias introduced by regularization while maintaining the efficiency benefits it provides. The significance of this research lies in its potential to enhance the performance of OT solvers, making them more accurate and effective in various applications.
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