5 citations · 9 across the 2 of their papers we have counts for
2 papers
stat.ML2020★ 5 cited
Meta-learning with Stochastic Linear Bandits
Leonardo Cella, Alessandro Lazaric, Massimiliano Pontil
We investigate meta-learning procedures in the setting of stochastic linear bandits tasks. The goal is to select a learning algorithm which works well on average over a class of ba…
stat.ML2019★ 4 cited
Stochastic Bandits with Delay-Dependent Payoffs
Leonardo Cella, Nicolò Cesa-Bianchi
Motivated by recommendation problems in music streaming platforms, we propose a nonstationary stochastic bandit model in which the expected reward of an arm depends on the number o…