update doc

Author: rflamary

docs/source/readme.rst

@@ -19,6 +19,7 @@ It provides the following solvers:
    squared L2 regularizations [17].
 -  Non regularized Wasserstein barycenters [16] with LP solver (only
    small scale).
+-  Non regularized free support Wasserstein barycenters [20].
 -  Bregman projections for Wasserstein barycenter [3] and unmixing [4].
 -  Optimal transport for domain adaptation with group lasso
    regularization [5]
@@ -29,6 +30,8 @@ It provides the following solvers:
    pymanopt).
 -  Gromov-Wasserstein distances and barycenters ([13] and regularized
    [12])
+-  Stochastic Optimization for Large-scale Optimal Transport (semi-dual
+   problem [18] and dual problem [19])
 
 Some demonstrations (both in Python and Jupyter Notebook format) are
 available in the examples folder.
@@ -219,6 +222,8 @@ The contributors to this library are:
 -  `Stanislas Chambon <https://slasnista.github.io/>`__
 -  `Antoine Rolet <https://arolet.github.io/>`__
 -  Erwan Vautier (Gromov-Wasserstein)
+-  `Kilian Fatras <https://kilianfatras.github.io/>`__ (Stochastic
+   optimization)
 
 This toolbox benefit a lot from open source research and we would like
 to thank the following persons for providing some code (in various
@@ -334,6 +339,20 @@ Optimal Transport <https://arxiv.org/abs/1710.06276>`__. Proceedings of
 the Twenty-First International Conference on Artificial Intelligence and
 Statistics (AISTATS).
 
+[18] Genevay, A., Cuturi, M., Peyré, G. & Bach, F. (2016) `Stochastic
+Optimization for Large-scale Optimal
+Transport <arXiv%20preprint%20arxiv:1605.08527>`__. Advances in Neural
+Information Processing Systems (2016).
+
+[19] Seguy, V., Bhushan Damodaran, B., Flamary, R., Courty, N., Rolet,
+A.& Blondel, M. `Large-scale Optimal Transport and Mapping
+Estimation <https://arxiv.org/pdf/1711.02283.pdf>`__. International
+Conference on Learning Representation (2018)
+
+[20] Cuturi, M. and Doucet, A. (2014) `Fast Computation of Wasserstein
+Barycenters <http://proceedings.mlr.press/v32/cuturi14.html>`__.
+International Conference in Machine Learning
+
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