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# POT Releases
## 0.5.0b
*Sep 2018*
*This is a beta release and is still a work in progress*
#### TODO
[] Remove deprecated OTDA Classes (PR #48)
[] Speedup Sinkhorn with einsum + bench (PR #58)
[] Stochastic ot (PR #62)
#### Features
* Add non regularized Gromov-Wasserstein solver (PR #41)
* Linear OT mapping between empirical distributions and 90\% test coverage (PR #42)
* Add log parameter in class EMDTransport and SinkhornLpL1Transport (PR #44)
* Add Marddown format for Pipy (PR #45)
* Test for Python 3.5 and 3.6 on Travis (PR #46)
* Non regularized Wasserstein barycenter with scipy linear solver and/or cvxopt (PR #47)
* Rename dataset functions to be more sklearn compliant (PR #49)
* Smooth and sparse Optimal transport implementation with entropic and quadratic regularization (PR #50)
* Stochastic OT in the dual and semi-dual (PR #52 and PR #62)
* Free support barycenters (PR #56)
* Speed-up Sinkhorn function (PR #57 and PR #58)
#### Closed issues
* Issue #35 : remove import plot from ot/__init__.py (See PR #41)
* Issue #43 : Unusable parameter log for EMDTransport (See PR #44)
* Issue #55 : UnicodeDecodeError: 'ascii' while installing with pip
## 0.4 Community edition
*15 Sep 2017*
This release contains a lot of contribution from new contributors.
#### Features
* Automatic notebooks and doc update (PR #27)
* Add gromov Wasserstein solver and Gromov Barycenters (PR #23)
* emd and emd2 can now return dual variables and have max_iter (PR #29 and PR #25)
* New domain adaptation classes compatible with scikit-learn (PR #22)
* Proper tests with pytest on travis (PR #19)
* PEP 8 tests (PR #13)
#### Closed issues
* emd convergence problem du to fixed max iterations (#24)
* Semi supervised DA error (#26)
## 0.3.1
*11 Jul 2017*
* Correct bug in emd on windows
## 0.3 Summer release
*7 Jul 2017*
* emd* and sinkhorn* are now performed in parallel for multiple target distributions
* emd and sinkhorn are for OT matrix computation
* emd2 and sinkhorn2 are for OT loss computation
* new notebooks for emd computation and Wasserstein Discriminant Analysis
* relocate notebooks
* update documentation
* clean_zeros(a,b,M) for removimg zeros in sparse distributions
* GPU implementations for sinkhorn and group lasso regularization
## V0.2
*7 Apr 2017*
* New dimensionality reduction method (WDA)
* Efficient method emd2 returns only tarnsport (in paralell if several histograms given)
## V0.1.11 New years resolution
*5 Jan 2017*
* Add sphinx gallery for better documentation
* Small efficiency tweak in sinkhorn
* Add simple tic() toc() functions for timing
## V0.1.10
*7 Nov 2016*
* numerical stabilization for sinkhorn (log domain and epsilon scaling)
## V0.1.9 DA classes and mapping
*4 Nov 2016*
* Update classes and examples for domain adaptation
* Joint OT matrix and mapping estimation
## V0.1.7
*31 Oct 2016*
* Original Domain adaptation classes
## PyPI version 0.1.3
* pipy works
## First pre-release
*28 Oct 2016*
It provides the following solvers:
* OT solver for the linear program/ Earth Movers Distance.
* Entropic regularization OT solver with Sinkhorn Knopp Algorithm.
* Bregman projections for Wasserstein barycenter [3] and unmixing.
* Optimal transport for domain adaptation with group lasso regularization
* Conditional gradient and Generalized conditional gradient for regularized OT.
Some demonstrations (both in Python and Jupyter Notebook format) are available in the examples folder.
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