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RELEASES.md

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# POT Releases
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## 0.4 Community edition
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* Add gromov Wasserstein solver and Gromov Barycenters (PR #23)
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* emd and emd2 can now return dual variables (PR #29)
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## 0.3.1
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*11 Jul 2017*
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* Correct bug in emd on windows
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## 0.3 Summer release
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*7 Jul 2017*
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* emd* and sinkhorn* are now performed in parallel for multiple target distributions
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* emd and sinkhorn are for OT matrix computation
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* emd2 and sinkhorn2 are for OT loss computation
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* new notebooks for emd computation and Wasserstein Discriminant Analysis
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* relocate notebooks
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* update documentation
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* clean_zeros(a,b,M) for removimg zeros in sparse distributions
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* GPU implementations for sinkhorn and group lasso regularization
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## V0.2
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*7 Apr 2017*
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* New dimensionality reduction method (WDA)
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* Efficient method emd2 returns only tarnsport (in paralell if several histograms given)
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## V0.1.11 New years resolution
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*5 Jan 2017*
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*28 Oct 2016*
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It provides the following solvers:
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* OT solver for the linear program/ Earth Movers Distance [1].
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* Entropic regularization OT solver with Sinkhorn Knopp Algorithm [2].
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* Bregman projections for Wasserstein barycenter [3] and unmixing [4].
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* Optimal transport for domain adaptation with group lasso regularization [5]
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* Conditional gradient [6] and Generalized conditional gradient for regularized OT [7].
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* OT solver for the linear program/ Earth Movers Distance.
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* Entropic regularization OT solver with Sinkhorn Knopp Algorithm.
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* Bregman projections for Wasserstein barycenter [3] and unmixing.
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* Optimal transport for domain adaptation with group lasso regularization
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* Conditional gradient and Generalized conditional gradient for regularized OT.
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Some demonstrations (both in Python and Jupyter Notebook format) are available in the examples folder.

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