351 citations · 1.2k across the 48 of their papers we have counts for
7 papers · 1 filter
Learning Disentangled Semantic Representation for Domain Adaptation
Ruichu Cai, Zijian Li, Pengfei Wei +3
Domain adaptation is an important but challenging task. Most of the existing domain adaptation methods struggle to extract the domain-invariant representation on the feature space…
Generalized Independent Noise Condition for Estimating Latent Variable Causal Graphs
Feng Xie, Ruichu Cai, Biwei Huang +3
Causal discovery aims to recover causal structures or models underlying the observed data. Despite its success in certain domains, most existing methods focus on causal relations b…
How Do Fair Decisions Fare in Long-term Qualification?
Xueru Zhang, Ruibo Tu, Yang Liu +4
Although many fairness criteria have been proposed for decision making, their long-term impact on the well-being of a population remains unclear. In this work, we study the dynamic…
On the Role of Sparsity and DAG Constraints for Learning Linear DAGs
Ignavier Ng, AmirEmad Ghassami, Kun Zhang
Learning graphical structures based on Directed Acyclic Graphs (DAGs) is a challenging problem, partly owing to the large search space of possible graphs. A recent line of work for…
A Causal View on Robustness of Neural Networks
Cheng Zhang, Kun Zhang, Yingzhen Li
We present a causal view on the robustness of neural networks against input manipulations, which applies not only to traditional classification tasks but also to general measuremen…
Learning from Positive and Unlabeled Data by Identifying the Annotation Process
Naji Shajarisales, Peter Spirtes, Kun Zhang
In binary classification, Learning from Positive and Unlabeled data (LePU) is semi-supervised learning but with labeled elements from only one class. Most of the research on LePU r…