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stat.ML2026
Sparse Dictionary Learning for Measure-Valued Data via Linearized Optimal Transport: Efficient Algorithms and Sample Complexity
Brendan Mallery, Shuchin Aeron, James Murphy
We study dictionary learning for probability measure-valued data by embedding measures into Hilbert spaces using features derived from optimal transport geometry. We learn data-ada…
stat.ML2026
Static and Dynamic Approaches to Computing Barycenters of Probability Measures on Graphs
David Gentile, James M. Murphy
The optimal transportation problem defines a geometry of probability measures which leads to a definition for weighted averages (barycenters) of measures, finding application in th…