79 citations · 137 across the 16 of their papers we have counts for
11 papers · 1 filter
Learning Optimal Antenna Tilt Control Policies: A Contextual Linear Bandit Approach
Filippo Vannella, Alexandre Proutiere, Yassir Jedra +1
Controlling antenna tilts in cellular networks is imperative to reach an efficient trade-off between network coverage and capacity. In this paper, we devise algorithms learning opt…
Minimal Expected Regret in Linear Quadratic Control
Yassir Jedra, Alexandre Proutiere
We consider the problem of online learning in Linear Quadratic Control systems whose state transition and state-action transition matrices and may be initially unknown. We…
Online Learning of Optimally Diverse Rankings
Stefan Magureanu, Alexandre Proutiere, Marcus Isaksson +1
Search engines answer users' queries by listing relevant items (e.g. documents, songs, products, web pages, ...). These engines rely on algorithms that learn to rank items so as to…
Regret Analysis in Deterministic Reinforcement Learning
Damianos Tranos, Alexandre Proutiere
We consider Markov Decision Processes (MDPs) with deterministic transitions and study the problem of regret minimization, which is central to the analysis and design of optimal lea…
Off-policy Learning for Remote Electrical Tilt Optimization
Filippo Vannella, Jaeseong Jeong, Alexandre Proutiere
We address the problem of Remote Electrical Tilt (RET) optimization using off-policy Contextual Multi-Armed-Bandit (CMAB) techniques. The goal in RET optimization is to control the…
Predictive Bandits
Simon Lindståhl, Alexandre Proutiere, Andreas Johnsson
We introduce and study a new class of stochastic bandit problems, referred to as predictive bandits. In each round, the decision maker first decides whether to gather information a…