69 citations · 235 across the 19 of their papers we have counts for
5 papers · 1 filter
What-is and How-to for Fairness in Machine Learning: A Survey, Reflection, and Perspective
Zeyu Tang, Jiji Zhang, Kun Zhang
Algorithmic fairness has attracted increasing attention in the machine learning community. Various definitions are proposed in the literature, but the differences and connections a…
Reliable Causal Discovery with Improved Exact Search and Weaker Assumptions
Ignavier Ng, Yujia Zheng, Jiji Zhang +1
Many of the causal discovery methods rely on the faithfulness assumption to guarantee asymptotic correctness. However, the assumption can be approximately violated in many ways, le…
On Low Rank Directed Acyclic Graphs and Causal Structure Learning
Zhuangyan Fang, Shengyu Zhu, Jiji Zhang +3
Despite several advances in recent years, learning causal structures represented by directed acyclic graphs (DAGs) remains a challenging task in high dimensional settings when the…
ASP-based Discovery of Semi-Markovian Causal Models under Weaker Assumptions
Zhalama, Jiji Zhang, Frederick Eberhardt +2
In recent years the possibility of relaxing the so-called Faithfulness assumption in automated causal discovery has been investigated. The investigation showed (1) that the Faithfu…
Causal Discovery from Heterogeneous/Nonstationary Data with Independent Changes
Biwei Huang, Kun Zhang, Jiji Zhang +4
It is commonplace to encounter heterogeneous or nonstationary data, of which the underlying generating process changes across domains or over time. Such a distribution shift featur…