Conti

Jean-Rémy Conti will be focusing on machine learning for spatial data. He will be setting a mathematical framework, in order to establish to what extent the rules obtained by empirical risk minimization can be generalized. It will also serve to study other extensions to the spatial context of popular algorithms, both theoretically and experientially. He is being supervised by Stéphan Clémençon, professor at Télécom Paris and Emilie Chautru, co-director of the geostatistics program and a researcher at the Ecole des Mines de Paris Geostatistics Center.

Keywords: machine learning for spatial data, mathematical, spatial context of popular algorithms, Geostatistics