collaborators

5 papers

stat.ML2019

Domain Generalization via Multidomain Discriminant Analysis

Shoubo Hu, Kun Zhang, Zhitang Chen +1

Domain generalization (DG) aims to incorporate knowledge from multiple source domains into a single model that could generalize well on unseen target domains. This problem is ubiqu…

stat.ML2018

A Kernel Embedding-based Approach for Nonstationary Causal Model Inference

Shoubo Hu, Zhitang Chen, Laiwan Chan

Although nonstationary data are more common in the real world, most existing causal discovery methods do not take nonstationarity into consideration. In this letter, we propose a k…

stat.ML2018

Causal Inference and Mechanism Clustering of A Mixture of Additive Noise Models

Shoubo Hu, Zhitang Chen, Vahid Partovi Nia +2

The inference of the causal relationship between a pair of observed variables is a fundamental problem in science, and most existing approaches are based on one single causal model…

stat.ML2018

Confounder Detection in High Dimensional Linear Models using First Moments of Spectral Measures

Furui Liu, Laiwan Chan

In this paper, we study the confounder detection problem in the linear model, where the target variable is predicted using its potential causes . Based…

stat.ML2018

Causal Inference on Discrete Data via Estimating Distance Correlations

Furui Liu, Laiwan Chan

In this paper, we deal with the problem of inferring causal directions when the data is on discrete domain. By considering the distribution of the cause and the conditional…