55 citations · 55 across the 4 of their papers we have counts for
4 papers · 1 filter
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…
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…
Out-of-distribution Generalization with Causal Invariant Transformations
Ruoyu Wang, Mingyang Yi, Zhitang Chen +1
In real-world applications, it is important and desirable to learn a model that performs well on out-of-distribution (OOD) data. Recently, causality has become a powerful tool to t…
Universal Hypothesis Testing with Kernels: Asymptotically Optimal Tests for Goodness of Fit
Shengyu Zhu, Biao Chen, Pengfei Yang +1
We characterize the asymptotic performance of nonparametric goodness of fit testing. The exponential decay rate of the type-II error probability is used as the asymptotic performan…