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Etienne Bamas

3 accepted papers

2020

Learning Augmented Energy Minimization via Speed Scaling

NeurIPS 2020spotlight

As power management has become a primary concern in modern data centers, computing resources are being scaled dynamically to minimize energy consumption. We initiate the study of a variant of the classic online speed scaling problem, in which machine learning predictions about the future can be inte…

2020

The Primal-Dual method for Learning Augmented Algorithms

NeurIPS 2020oral

The extension of classical online algorithms when provided with predictions is a new and active research area. In this paper, we extend the primal-dual method for online algorithms in order to incorporate predictions that advise the online algorithm about the next action to take. We use this framewo…