3 papers
stat.ML2024
Causal Discovery by Kernel Deviance Measures with Heterogeneous Transforms
Tim Tse, Zhitang Chen, Shengyu Zhu +1
The discovery of causal relationships in a set of random variables is a fundamental objective of science and has also recently been argued as being an essential component towards r…
stat.ML2024
Causal Coordinated Concurrent Reinforcement Learning
Tim Tse, Isaac Chan, Zhitang Chen
In this work, we propose a novel algorithmic framework for data sharing and coordinated exploration for the purpose of learning more data-efficient and better performing policies u…
cs.LG2019
Causal Discovery by Kernel Intrinsic Invariance Measure
Zhitang Chen, Shengyu Zhu, Yue Liu +1
Reasoning based on causality, instead of association has been considered as a key ingredient towards real machine intelligence. However, it is a challenging task to infer causal re…