1 citations · 1 across the 1 of their papers we have counts for
3 papers
cs.LG2021★ 1 cited
Privacy-Preserving Communication-Efficient Federated Multi-Armed Bandits
Tan Li, Linqi Song
Communication bottleneck and data privacy are two critical concerns in federated multi-armed bandit (MAB) problems, such as situations in decision-making and recommendations of con…
cs.AI2020
Distributed Thompson Sampling
Jing Dong, Tan Li, Shaolei Ren +1
We study a cooperative multi-agent multi-armed bandits with M agents and K arms. The goal of the agents is to minimized the cumulative regret. We adapt a traditional Thompson Sampl…
cs.LG2020
Federated Recommendation System via Differential Privacy
Tan Li, Linqi Song, Christina Fragouli
In this paper, we are interested in what we term the federated private bandits framework, that combines differential privacy with multi-agent bandit learning. We explore how differ…