7 citations · 22 across the 10 of their papers we have counts for
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cs.LG2021★ 3 cited
Multimodal Reward Shaping for Efficient Exploration in Reinforcement Learning
Mingqi Yuan, Mon-on Pun, Dong Wang +2
Maintaining the long-term exploration capability of the agent remains one of the critical challenges in deep reinforcement learning. A representative solution is to leverage reward…
cs.LG2021★ 7 cited
Assessing Fairness in Classification Parity of Machine Learning Models in Healthcare
Ming Yuan, Vikas Kumar, Muhammad Aurangzeb Ahmad +1
Fairness in AI and machine learning systems has become a fundamental problem in the accountability of AI systems. While the need for accountability of AI models is near ubiquitous,…
cs.LG2021
Exploring Beyond-Demonstrator via Meta Learning-Based Reward Extrapolation
Mingqi Yuan, Mao-on Pun
Extrapolating beyond-demonstrator (BD) performance through the imitation learning (IL) algorithm aims to learn from and subsequently outperform the demonstrator. To that end, a rep…