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An Efficient Orlicz-Sobolev Approach for Transporting Unbalanced Measures on a Graph

arXiv — cs.LG•Monday, October 27, 2025 at 4:00:00 AM
PositiveArtificial Intelligence
A new study explores an innovative approach to optimal transport for measures on graph metric spaces, addressing the challenges posed by traditional methods. By utilizing Orlicz-Wasserstein and generalized Sobolev transport, the research introduces a fresh geometric perspective that enhances machine learning techniques. This advancement is significant as it opens up new possibilities for handling unbalanced measures, which is crucial for various applications in data science and optimization.
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