2 citations · 3 across the 3 of their papers we have counts for
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cs.LG2023★ 1 cited
Provably Feedback-Efficient Reinforcement Learning via Active Reward Learning
Dingwen Kong, Lin F. Yang
An appropriate reward function is of paramount importance in specifying a task in reinforcement learning (RL). Yet, it is known to be extremely challenging in practice to design a…
cs.LG2022
Learning Rationalizable Equilibria in Multiplayer Games
Yuanhao Wang, Dingwen Kong, Yu Bai +1
A natural goal in multiagent learning besides finding equilibria is to learn rationalizable behavior, where players learn to avoid iteratively dominated actions. However, even in t…
cs.LG2021★ 2 cited
Online Sub-Sampling for Reinforcement Learning with General Function Approximation
Dingwen Kong, Ruslan Salakhutdinov, Ruosong Wang +1
Most of the existing works for reinforcement learning (RL) with general function approximation (FA) focus on understanding the statistical complexity or regret bounds. However, the…