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Section: Partnerships and Cooperations
International Initiatives
Inria International Partners
Informal International Partners
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We maintain a strong line of collaborations with the Technical University Federico Santa María (UTFSM), Valparaíso, Chile. Over the years, this has taken different forms (associated team Manap, Stic AmSud project “AMMA”, Stic AmSud project “DAT”). In 2017, we had a joint PhD work running (PhD of Nicolás Jara, to be defended at the beginning of next year), and a new joint PhD to be started in 2018 (PhD of Jonathan Olavarría). The first one is on optical network analysis and design, the second one on modeling evaluation techniques, with focus on Stochastic Activity Networks.
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We started a collaboration with the Faculty of Sciences of the university of the Republic, in Uruguay, on the application of mathematical modeling tools to a better understanding of a cognitive disease called semantic dementia. This involves Prof. Eduardo Mizraji and Jorge Graneri, PhD student, whose co-advisors are Prof. Mizraji and G. Rubino from Dionysos. Our contribution to this project is around the use of mathematical models, in particular around neural structures.
Participation in Other International Programs
International Initiatives
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Title: Statistical methods for highly complex and/or high dimensional data
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International Partner (Institution - Laboratory - Researcher):
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In this project we work on specific statistical tools, mainly concerning predicting the behavior of time series. Our goal is to improve our tools for Perceptual Quality evaluation.
International Initiatives
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Title: Monte Carlo and Quasi- Monte Carlo for rare event simulation
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International Partner (Institution - Laboratory - Researcher):
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See also: http://www.irisa.fr/dionysos/pages_perso/tuffin/MOCQUASIN/
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The goal of this team is to compute integrals, sums or to solve equations or optimization problems by means of Monte Carlo methods, which are statistical tools used when the models have a high complexity (for instance a large dimension). They are unavoidable tools in areas such as finance, electronics, seismology, computer science, engineering, physics, transport, biology, social sciences... Nonetheless, they have the reputation of being slow, i.e. to require a large computational time to reach a given precision. The goal of the project is to work on acceleration techniques, meaning methods allowing to reach the targeted precision in a shorter computational time. A typical framework is that of rare event simulation for which getting even only one occurrence of the event of interest could require a very long time. In this case, there are two main acceleration techniques: importance sampling and splitting, on which we work.