cleanup reference years in readme

2 files changed, 14 insertions, 14 deletions

diff --git a/README.md b/README.md
index 65ee710..6b7cff0 100644
--- a/README.md
+++ b/README.md
@@ -195,7 +195,7 @@ You can also post bug reports and feature requests in Github issues. Make sure t
 
 [7] Rakotomamonjy, A., Flamary, R., & Courty, N. (2015). [Generalized conditional gradient: analysis of convergence and applications](https://arxiv.org/pdf/1510.06567.pdf). arXiv preprint arXiv:1510.06567.
 
-[8] M. Perrot, N. Courty, R. Flamary, A. Habrard, [Mapping estimation for discrete optimal transport](http://remi.flamary.com/biblio/perrot2016mapping.pdf), Neural Information Processing Systems (NIPS), 2016.
+[8] M. Perrot, N. Courty, R. Flamary, A. Habrard (2016), [Mapping estimation for discrete optimal transport](http://remi.flamary.com/biblio/perrot2016mapping.pdf), Neural Information Processing Systems (NIPS).
 
 [9] Schmitzer, B. (2016). [Stabilized Sparse Scaling Algorithms for Entropy Regularized Transport Problems](https://arxiv.org/pdf/1610.06519.pdf). arXiv preprint arXiv:1610.06519.
 
@@ -203,10 +203,10 @@ You can also post bug reports and feature requests in Github issues. Make sure t
 
 [11] Flamary, R., Cuturi, M., Courty, N., & Rakotomamonjy, A. (2016). [Wasserstein Discriminant Analysis](https://arxiv.org/pdf/1608.08063.pdf). arXiv preprint arXiv:1608.08063.
 
-[12] Gabriel Peyré, Marco Cuturi, and Justin Solomon, [Gromov-Wasserstein averaging of kernel and distance matrices](http://proceedings.mlr.press/v48/peyre16.html)  International Conference on Machine Learning (ICML). 2016.
+[12] Gabriel Peyré, Marco Cuturi, and Justin Solomon (2016), [Gromov-Wasserstein averaging of kernel and distance matrices](http://proceedings.mlr.press/v48/peyre16.html)  International Conference on Machine Learning (ICML).
 
-[13] Mémoli, Facundo. [Gromov–Wasserstein distances and the metric approach to object matching](https://media.adelaide.edu.au/acvt/Publications/2011/2011-Gromov%E2%80%93Wasserstein%20Distances%20and%20the%20Metric%20Approach%20to%20Object%20Matching.pdf). Foundations of computational mathematics 11.4 (2011): 417-487.
+[13] Mémoli, Facundo (2011). [Gromov–Wasserstein distances and the metric approach to object matching](https://media.adelaide.edu.au/acvt/Publications/2011/2011-Gromov%E2%80%93Wasserstein%20Distances%20and%20the%20Metric%20Approach%20to%20Object%20Matching.pdf). Foundations of computational mathematics 11.4 : 417-487.
 
-[14] Knott, M. and Smith, C. S. [On the optimal mapping of distributions](https://link.springer.com/article/10.1007/BF00934745), Journal of Optimization Theory and Applications Vol 43, 1984.
+[14] Knott, M. and Smith, C. S. (1984).[On the optimal mapping of distributions](https://link.springer.com/article/10.1007/BF00934745), Journal of Optimization Theory and Applications Vol 43.
 
 [15] Peyré, G., & Cuturi, M. (2018). [Computational Optimal Transport](https://arxiv.org/pdf/1803.00567.pdf) .
diff --git a/docs/source/readme.rst b/docs/source/readme.rst
index d73d293..725c207 100644
--- a/docs/source/readme.rst
+++ b/docs/source/readme.rst
@@ -283,10 +283,10 @@ conditional gradient: analysis of convergence and
 applications <https://arxiv.org/pdf/1510.06567.pdf>`__. arXiv preprint
 arXiv:1510.06567.
 
-[8] M. Perrot, N. Courty, R. Flamary, A. Habrard, `Mapping estimation
-for discrete optimal
+[8] M. Perrot, N. Courty, R. Flamary, A. Habrard (2016), `Mapping
+estimation for discrete optimal
 transport <http://remi.flamary.com/biblio/perrot2016mapping.pdf>`__,
-Neural Information Processing Systems (NIPS), 2016.
+Neural Information Processing Systems (NIPS).
 
 [9] Schmitzer, B. (2016). `Stabilized Sparse Scaling Algorithms for
 Entropy Regularized Transport
@@ -303,19 +303,19 @@ arXiv:1607.05816.
 Analysis <https://arxiv.org/pdf/1608.08063.pdf>`__. arXiv preprint
 arXiv:1608.08063.
 
-[12] Gabriel Peyré, Marco Cuturi, and Justin Solomon,
+[12] Gabriel Peyré, Marco Cuturi, and Justin Solomon (2016),
 `Gromov-Wasserstein averaging of kernel and distance
 matrices <http://proceedings.mlr.press/v48/peyre16.html>`__
-International Conference on Machine Learning (ICML). 2016.
+International Conference on Machine Learning (ICML).
 
-[13] Mémoli, Facundo. `Gromov–Wasserstein distances and the metric
-approach to object
+[13] Mémoli, Facundo (2011). `Gromov–Wasserstein distances and the
+metric approach to object
 matching <https://media.adelaide.edu.au/acvt/Publications/2011/2011-Gromov%E2%80%93Wasserstein%20Distances%20and%20the%20Metric%20Approach%20to%20Object%20Matching.pdf>`__.
-Foundations of computational mathematics 11.4 (2011): 417-487.
+Foundations of computational mathematics 11.4 : 417-487.
 
-[14] Knott, M. and Smith, C. S. `On the optimal mapping of
+[14] Knott, M. and Smith, C. S. (1984).`On the optimal mapping of
 distributions <https://link.springer.com/article/10.1007/BF00934745>`__,
-Journal of Optimization Theory and Applications Vol 43, 1984.
+Journal of Optimization Theory and Applications Vol 43.
 
 [15] Peyré, G., & Cuturi, M. (2018). `Computational Optimal
 Transport <https://arxiv.org/pdf/1803.00567.pdf>`__ .