23 citations · 28 across the 2 of their papers we have counts for
3 papers
cs.LG2020
Stochastic Bandits with Vector Losses: Minimizing -Norm of Relative Losses
Xuedong Shang, Han Shao, Jian Qian
Multi-armed bandits are widely applied in scenarios like recommender systems, for which the goal is to maximize the click rate. However, more factors should be considered, e.g., us…
stat.ML2020★ 23 cited
Gamification of Pure Exploration for Linear Bandits
Rémy Degenne, Pierre Ménard, Xuedong Shang +1
We investigate an active pure-exploration setting, that includes best-arm identification, in the context of linear stochastic bandits. While asymptotically optimal algorithms exist…
cs.LG2019★ 5 cited
Fixed-Confidence Guarantees for Bayesian Best-Arm Identification
Xuedong Shang, Rianne de Heide, Emilie Kaufmann +2
We investigate and provide new insights on the sampling rule called Top-Two Thompson Sampling (TTTS). In particular, we justify its use for fixed-confidence best-arm identification…