10 citations · 16 across the 4 of their papers we have counts for
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cs.LG2020★ 2 cited
Supervised Whole DAG Causal Discovery
Hebi Li, Qi Xiao, Jin Tian
We propose to address the task of causal structure learning from data in a supervised manner. Existing work on learning causal directions by supervised learning is restricted to le…
cs.LG2019
Adjustment Criteria for Recovering Causal Effects from Missing Data
Mojdeh Saadati, Jin Tian
Confounding bias, missing data, and selection bias are three common obstacles to valid causal inference in the data sciences. Covariate adjustment is the most pervasive technique f…
cs.LG2019★ 3 cited
Purifying Adversarial Perturbation with Adversarially Trained Auto-encoders
Hebi Li, Qi Xiao, Shixin Tian +1
Machine learning models are vulnerable to adversarial examples. Iterative adversarial training has shown promising results against strong white-box attacks. However, adversarial tr…