Update README

README.md

@@ -2,7 +2,7 @@
 
 This repository implements the Screen & Relax method solving the Elastic-Net problem. We introduced this method in the paper
 
-> Théo Guyard, Cédric Herzet, Clément Elvira, *Screen & Relax: Accelerating the resolution of Elastic-net by safe identification of the solution support*
+> Guyard, T., Herzet, C., & Elvira, C. (2022, May). Screen & relax: accelerating the resolution of Elastic-Net by safe identification of the solution support. In *ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)* (pp. 5443-5447). IEEE.
 
 available [here](https://arxiv.org/pdf/2110.07281.pdf). This paper contains theoretical and numerical results that can be reproduced with this toolbox. If you encounter a bug or something unexpected, please let me know by raising an issue on the project page or by contacting me by [mail](mailto:theo.guyard@insa-rennes.fr).
 
@@ -43,7 +43,7 @@ pip install .
 
 ## ICASSP experiments
 
-Experiments presented in the Screen & Relax paper submitted at [ICASSP 2022](https://2022.ieeeicassp.org) are located in the folder `screen-and-relax/exp/ICASSP/`. The two available experiments are 
+Experiments presented in the Screen & Relax paper submitted to [ICASSP 2022](https://2022.ieeeicassp.org) are located in the folder `screen-and-relax/exp/ICASSP/`. The two available experiments are 
 * `convergence.py` : convergence of the four compared methods on a single problem instance
 * `performance_profiles.py` : figure 1 of the "Screen & Relax" paper
 
@@ -75,11 +75,12 @@ This software is distributed under the [MIT Licence](https://mit-license.org).
 If you use this package for your own work, please consider citing it as :
 
 ```bibtex
-@article{guyard2021screen,
-  title={Screen \& Relax: Accelerating the resolution of Elastic-net by safe identification of the solution support},
+@inproceedings{guyard2022screen,
+  title={Screen \& relax: accelerating the resolution of Elastic-Net by safe identification of the solution support},
   author={Guyard, Th{\'e}o and Herzet, C{\'e}dric and Elvira, Cl{\'e}ment},
-  journal={arXiv preprint arXiv:2110.07281},
-  year={2021}
+  booktitle={ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
+  pages={5443--5447},
+  year={2022},
+  organization={IEEE}
 }
-
 ```