17 citations · 65 across the 12 of their papers we have counts for
6 papers · 1 filter
Towards Return Parity in Markov Decision Processes
Jianfeng Chi, Jian Shen, Xinyi Dai +3
Algorithmic decisions made by machine learning models in high-stakes domains may have lasting impacts over time. However, naive applications of standard fairness criterion in stati…
On Effective Scheduling of Model-based Reinforcement Learning
Hang Lai, Jian Shen, Weinan Zhang +5
Model-based reinforcement learning has attracted wide attention due to its superior sample efficiency. Despite its impressive success so far, it is still unclear how to appropriate…
Curriculum Offline Imitation Learning
Minghuan Liu, Hanye Zhao, Zhengyu Yang +4
Offline reinforcement learning (RL) tasks require the agent to learn from a pre-collected dataset with no further interactions with the environment. Despite the potential to surpas…
Task-wise Split Gradient Boosting Trees for Multi-center Diabetes Prediction
Mingcheng Chen, Zhenghui Wang, Zhiyun Zhao +14
Diabetes prediction is an important data science application in the social healthcare domain. There exist two main challenges in the diabetes prediction task: data heterogeneity si…
MapGo: Model-Assisted Policy Optimization for Goal-Oriented Tasks
Menghui Zhu, Minghuan Liu, Jian Shen +7
In Goal-oriented Reinforcement learning, relabeling the raw goals in past experience to provide agents with hindsight ability is a major solution to the reward sparsity problem. In…
Model-based Multi-agent Policy Optimization with Adaptive Opponent-wise Rollouts
Weinan Zhang, Xihuai Wang, Jian Shen +1
This paper investigates the model-based methods in multi-agent reinforcement learning (MARL). We specify the dynamics sample complexity and the opponent sample complexity in MARL,…