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20182021
most citedOn Asymptotically Tight Tail Bounds for Sums of Geometric and Exponential Random Variables

4 citations · 8 across the 5 of their papers we have counts for

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stat.ML2019

Tight Regret Bounds for Infinite-armed Linear Contextual Bandits

Yingkai Li, Yining Wang, Xi Chen +1

Linear contextual bandit is an important class of sequential decision making problems with a wide range of applications to recommender systems, online advertising, healthcare, and…

stat.ML2019

Nearly Minimax-Optimal Regret for Linearly Parameterized Bandits

Yingkai Li, Yining Wang, Yuan Zhou

We study the linear contextual bandit problem with finite action sets. When the problem dimension is , the time horizon is , and there are candidate actions…