97 citations · 100 across the 7 of their papers we have counts for
7 papers
Agent-Aware Training for Agent-Agnostic Action Advising in Deep Reinforcement Learning
Yaoquan Wei, Shunyu Liu, Jie Song +4
Action advising endeavors to leverage supplementary guidance from expert teachers to alleviate the issue of sampling inefficiency in Deep Reinforcement Learning (DRL). Previous age…
Curricular Subgoals for Inverse Reinforcement Learning
Shunyu Liu, Yunpeng Qing, Shuqi Xu +6
Inverse Reinforcement Learning (IRL) aims to reconstruct the reward function from expert demonstrations to facilitate policy learning, and has demonstrated its remarkable success i…
Attention Diversification for Domain Generalization
Rang Meng, Xianfeng Li, Weijie Chen +7
Convolutional neural networks (CNNs) have demonstrated gratifying results at learning discriminative features. However, when applied to unseen domains, state-of-the-art models are…
A Survey of Neural Trees
Haoling Li, Jie Song, Mengqi Xue +4
Neural networks (NNs) and decision trees (DTs) are both popular models of machine learning, yet coming with mutually exclusive advantages and limitations. To bring the best of the…
Distribution-Aware Graph Representation Learning for Transient Stability Assessment of Power System
Kaixuan Chen, Shunyu Liu, Na Yu +5
The real-time transient stability assessment (TSA) plays a critical role in the secure operation of the power system. Although the classic numerical integration method, \textit{i.e…
Spot-adaptive Knowledge Distillation
Jie Song, Ying Chen, Jingwen Ye +1
Knowledge distillation (KD) has become a well established paradigm for compressing deep neural networks. The typical way of conducting knowledge distillation is to train the studen…