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- W651076980 abstract "We propose a method based on optimal transport for empirical distributions with Laplacian regularization (LOT). Laplacian regularization is a graph-based regu-larization that can encode neighborhood similarity between samples either on the final position of the transported samples or on their displacement. In both cases, LOT is expressed as a quadratic programming problem and can be solved with a Frank-Wolfe algorithm with optimal step size. Result on domain adaptation and a shape matching problems show the interest of using this regularization in optimal transport." @default.
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- W651076980 date "2014-12-01" @default.
- W651076980 modified "2023-10-03" @default.
- W651076980 title "Optimal transport with Laplacian regularization" @default.
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