3 citations · 8 across the 7 of their papers we have counts for
4 papers · 1 filter
Rethinking State Disentanglement in Causal Reinforcement Learning
Haiyao Cao, Zhen Zhang, Panpan Cai +7
One of the significant challenges in reinforcement learning (RL) when dealing with noise is estimating latent states from observations. Causality provides rigorous theoretical supp…
Optimal Kernel Choice for Score Function-based Causal Discovery
Wenjie Wang, Biwei Huang, Feng Liu +4
Score-based methods have demonstrated their effectiveness in discovering causal relationships by scoring different causal structures based on their goodness of fit to the data. Rec…
Interventional Fairness on Partially Known Causal Graphs: A Constrained Optimization Approach
Aoqi Zuo, Yiqing Li, Susan Wei +1
Fair machine learning aims to prevent discrimination against individuals or sub-populations based on sensitive attributes such as gender and race. In recent years, causal inference…
Diversity-enhancing Generative Network for Few-shot Hypothesis Adaptation
Ruijiang Dong, Feng Liu, Haoang Chi +5
Generating unlabeled data has been recently shown to help address the few-shot hypothesis adaptation (FHA) problem, where we aim to train a classifier for the target domain with a…