Section: Partnerships and Cooperations

International Initiatives

Inria Associate Teams Not Involved in an Inria International Labs

  • Title: Machine Learning for Network Analytics

  • International Partner (Institution - Laboratory - Researcher):

    • Indian Institute of Technology Bombay (India) - Electrical Communication Engineering - Vivek Borkar

  • Start year: 2017

  • See also: http://www-sop.inria.fr/members/Konstantin.Avratchenkov/MALENA.html

  • In the past couple of decades network science has seen an explosive growth, enough to be identified as a discipline of its own, overlapping with engineering, physics, biology, economics and social sciences. Much effort has gone into modelling, performance measures, classification of emergent features and phenomena, etc, particularly in natural and social sciences. The algorithmic side, all important to engineers, has been recognised as a thrust area (e.g., two recent Nevanlinna Prize (J. Kleinberg 2006 and D. Spielman 2010) went to prominent researchers in the area of network analytics). Still, in our opinion the area is yet to mature and has a lot of uncharted territory. This is because networks provide a highly varied landscape, each flavour demanding different considerations (e.g., sparse vs dense graphs, Erdos-Renyi vs planted partition graphs, standard graphs vs hypergraphs, etc). Even adopting existing methodologies to these novel situations is often a nontrivial exercise, not to mention many problems that cry out for entirely new algorithmic paradigms. It is in this context that we propose this project of developing algorithmic tools, drawing not only upon established as well as novel methodologies in machine learning and big data analytics, but going well beyond, e.g., into statistical physics tools.

  • Title: THeory and Application of NEtwork Science

  • International Partner (Institution - Laboratory - Researcher):

    • Universidade Federal do Rio de Janeiro (Brazil) - Computer Science Department - Daniel Ratton Figueiredo

  • Start year: 2017

  • See also: https://team.inria.fr/thanes/

  • This team is the follow-up of a joint Inria-UFRJ team (funded by FAPERJ in Rio de Janeiro, Brazil) with the same name and almost the same permanent researchers involved. During the first three years THANES has studied how services in Online Social Networks (OSNs) can be efficiently designed and managed. The joint research activity continued along the line of network science with a focus on network growth models, community detection, information spreading, and recommendation systems for online social networks. A new research axis on deep learning spawned during 2018.

Participation in Other International Programs

Indo-French Center of Applied Mathematics (IFCAM)

Neo is involved in the IFCAM with the MALENA project. See