New Inria grant
The “exploratory action” MAMMALS, Memory-augmented Models for low-latency Machine-learning Serving, proposed by Giovanni Neglia, has been granted by Inria. Read its description.
The “exploratory action” MAMMALS, Memory-augmented Models for low-latency Machine-learning Serving, proposed by Giovanni Neglia, has been granted by Inria. Read its description.
NEO signs a research convention with Accenture on the topic of Machine Learning fo IoT applications.
Maximilien Dreveton, PhD student in NEO, has co-authored a book: Leçons pour l’agrégation de mathématiques. Congratulations!
NEO has signed a research convention with the Payback Network company. This convention involves also the EPIONE team.
Eitan Altman obtained the funding of a postdoctoral position from the Gaspard Monge Program for Optimization, a program from the Hadamard Foundation. The topic is “Game Theoretical Tools for Pricing the Grid”. Congratulations!
Topic: optimal decision for prefetching under uncertainty Supervisors: Alain Jean-Marie, Sara Alouf, Inria NEO project-team, Sophia Antipolis Place: Sophia-Antipolis. Résumé: Prefetching is a basic technique used to reduce the latency of diverse computer services. Its principle is to bring proactively…