6 citations · 6 across the 3 of their papers we have counts for
3 papers
Non-Stationary Gradient Descent for Optimal Auto-Scaling in Serverless Platforms
Jonatha Anselmi, Bruno Gaujal, Louis-Sebastien Rebuffi
To efficiently manage serverless computing platforms, a key aspect is the auto-scaling of services, i.e., the set of computational resources allocated to a service adapts over time…
Learning Optimal Admission Control in Partially Observable Queueing Networks
Jonatha Anselmi, Bruno Gaujal, Louis-Sébastien Rebuffi
We present an efficient reinforcement learning algorithm that learns the optimal admission control policy in a partially observable queueing network. Specifically, only the arrival…
Reinforcement Learning in a Birth and Death Process: Breaking the Dependence on the State Space
Jonatha Anselmi, Bruno Gaujal, Louis-Sébastien Rebuffi
In this paper, we revisit the regret of undiscounted reinforcement learning in MDPs with a birth and death structure. Specifically, we consider a controlled queue with impatient jo…