Merge pull request #643 from marcwitasee/patch-3

Fix bad citation ref in e2clab_project.md

_projects/e2clab_project.md

@@ -168,7 +168,7 @@ On the ANL side, we continued our investment in reproducibility topics by engagi
 
 Over the summer of 2023, members of the REPETO project hosted the first Summer of Reproducibility program. The program offers summer internship opportunities for students and mentors who are interested in reproducibility for computer science research. It is modeled on Google Summer of Code: mentors propose a project and students apply for it. We particularly sponsor projects that package experiments to advance practical reproducibility, i.e., the idea that reproducibility can be a mainstream method of scientific exploration, similar to what reading papers is today. Those experiments can be replayed -- and potentially modified and improved to propose and test new ideas -- on Chameleon. The program provides funding for both US-based and international students and collaborations. In 2024, the REPETO project will continue to support the Summer of Reproducibility initiative and a call for projects for this summer is already underway.
 
-The discussions of edge computing are emergent with both INRIA and ANL making separate investigations for the time being. The ANL team is working in the context of the CHI@Edge platform on Chameleon {% cite Chi@Edge2024 --file external/e2clab_project.bib %} and FLOTO projects {% cite KeaheyEtAl2023b --file external/e2clab_project.bib %}. The INRIA team is focusing on two challenges: (1) the efficient provenance data capture at the edge, for reproducibility purposes {% cite RosendoEtAl2023b --file external/e2clab_project.bib %}, and (2) enabling continual learning and federated learning at the edge, in the context of the ENGAGE project {% cite Engage2024 --file external/e2clab_project.bib %}, where initial results target the efficient deployment of such workloads on the edge-cloud continuum {% cite PrigentEtAl2022 --file external/e2clab_project.bib %} and securing the learning in the heterogeneous and volatile edge environments {% cite ChelliEtAl2023 --file external/e2clab_project.bib %}.
+The discussions of edge computing are emergent with both INRIA and ANL making separate investigations for the time being. The ANL team is working in the context of the CHI@Edge platform on Chameleon {% cite ChiEdge2024 --file external/e2clab_project.bib %} and FLOTO projects {% cite KeaheyEtAl2023b --file external/e2clab_project.bib %}. The INRIA team is focusing on two challenges: (1) the efficient provenance data capture at the edge, for reproducibility purposes {% cite RosendoEtAl2023b --file external/e2clab_project.bib %}, and (2) enabling continual learning and federated learning at the edge, in the context of the ENGAGE project {% cite Engage2024 --file external/e2clab_project.bib %}, where initial results target the efficient deployment of such workloads on the edge-cloud continuum {% cite PrigentEtAl2022 --file external/e2clab_project.bib %} and securing the learning in the heterogeneous and volatile edge environments {% cite ChelliEtAl2023 --file external/e2clab_project.bib %}.
 
 
 ## Visits and meetings