28 citations · 35 across the 5 of their papers we have counts for
5 papers
Fair Causal Feature Selection
Zhaolong Ling, Enqi Xu, Peng Zhou +3
Fair feature selection for classification decision tasks has recently garnered significant attention from researchers. However, existing fair feature selection algorithms fall shor…
Feature Selection for Efficient Local-to-Global Bayesian Network Structure Learning
Kui Yu, Zhaolong Ling, Lin Liu +2
Local-to-global learning approach plays an essential role in Bayesian network (BN) structure learning. Existing local-to-global learning algorithms first construct the skeleton of…
Any Part of Bayesian Network Structure Learning
Zhaolong Ling, Kui Yu, Hao Wang +2
We study an interesting and challenging problem, learning any part of a Bayesian network (BN) structure. In this challenge, it will be computationally inefficient using existing gl…
Causal Learner: A Toolbox for Causal Structure and Markov Blanket Learning
Zhaolong Ling, Kui Yu, Yiwen Zhang +2
Causal Learner is a toolbox for learning causal structure and Markov blanket (MB) from data. It integrates functions for generating simulated Bayesian network data, a set of state-…
Causality-based Feature Selection: Methods and Evaluations
Kui Yu, Xianjie Guo, Lin Liu +4
Feature selection is a crucial preprocessing step in data analytics and machine learning. Classical feature selection algorithms select features based on the correlations between p…