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author | Rémi Flamary <remi.flamary@gmail.com> | 2018-05-31 13:03:40 +0200 |
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committer | Rémi Flamary <remi.flamary@gmail.com> | 2018-05-31 13:03:40 +0200 |
commit | ed0d4171c6291a15360bdb8a955b0783585da749 (patch) | |
tree | bc9e63e628ce3138d3ad8547115559ab7b1496a2 /README.md | |
parent | 10f9b0d1b02c2b5f4c4eeac0c1f803657c89764b (diff) |
update readme
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-rw-r--r-- | README.md | 3 |
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@@ -15,6 +15,7 @@ It provides the following solvers: * OT Network Flow solver for the linear program/ Earth Movers Distance [1]. * Entropic regularization OT solver with Sinkhorn Knopp Algorithm [2] and stabilized version [9][10] with optional GPU implementation (requires cudamat). +* Smooth optimal transport solvers (dual and semi-dual) for KL and squared L2 regularization [17]. * Non regularized Wasserstein barycenters [16] with LP solver. * Bregman projections for Wasserstein barycenter [3] and unmixing [4]. * Optimal transport for domain adaptation with group lasso regularization [5] @@ -213,3 +214,5 @@ You can also post bug reports and feature requests in Github issues. Make sure t [15] Peyré, G., & Cuturi, M. (2018). [Computational Optimal Transport](https://arxiv.org/pdf/1803.00567.pdf) . [16] Agueh, M., & Carlier, G. (2011). [Barycenters in the Wasserstein space](https://hal.archives-ouvertes.fr/hal-00637399/document). SIAM Journal on Mathematical Analysis, 43(2), 904-924. + +[17] Blondel, M., Seguy, V., & Rolet, A. (2018). [Smooth and Sparse Optimal Transport](https://arxiv.org/abs/1710.06276). Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics (AISTATS). |