25 citations · 75 across the 12 of their papers we have counts for
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stat.ML2019★ 11 cited
Provably Efficient Reinforcement Learning with Aggregated States
Shi Dong, Benjamin Van Roy, Zhengyuan Zhou
We establish that an optimistic variant of Q-learning applied to a fixed-horizon episodic Markov decision process with an aggregated state representation incurs regret $\tilde{\mat…
cs.LG2019★ 25 cited
Comments on the Du-Kakade-Wang-Yang Lower Bounds
Benjamin Van Roy, Shi Dong
Du, Kakade, Wang, and Yang recently established intriguing lower bounds on sample complexity, which suggest that reinforcement learning with a misspecified representation is intrac…
stat.ML2019★ 4 cited
On the Performance of Thompson Sampling on Logistic Bandits
Shi Dong, Tengyu Ma, Benjamin Van Roy
We study the logistic bandit, in which rewards are binary with success probability and actions and coefficients are within the …