4 citations · 7 across the 4 of their papers we have counts for
4 papers
Specify Robust Causal Representation from Mixed Observations
Mengyue Yang, Xinyu Cai, Furui Liu +2
Learning representations purely from observations concerns the problem of learning a low-dimensional, compact representation which is beneficial to prediction models. Under the hyp…
Generalizable Information Theoretic Causal Representation
Mengyue Yang, Xinyu Cai, Furui Liu +4
It is evidence that representation learning can improve model's performance over multiple downstream tasks in many real-world scenarios, such as image classification and recommende…
Seeing Differently, Acting Similarly: Heterogeneously Observable Imitation Learning
Xin-Qiang Cai, Yao-Xiang Ding, Zi-Xuan Chen +3
In many real-world imitation learning tasks, the demonstrator and the learner have to act under different observation spaces. This situation brings significant obstacles to existin…
Imitation Learning from Pixel-Level Demonstrations by HashReward
Xin-Qiang Cai, Yao-Xiang Ding, Yuan Jiang +1
One of the key issues for imitation learning lies in making policy learned from limited samples to generalize well in the whole state-action space. This problem is much more severe…