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stat.ML2026
Fairness under Graph Uncertainty: Achieving Interventional Fairness with Partially Known Causal Graphs over Clusters of Variables
Yoichi Chikahara
Algorithmic decisions about individuals require predictions that are not only accurate but also fair with respect to sensitive attributes such as gender and race. Causal notions of…
stat.ML2026
Moment Matters: Mean and Variance Causal Graph Discovery from Heteroscedastic Observational Data
Yoichi Chikahara
Heteroscedasticity -- where the variance of a variable changes with other variables -- is pervasive in real data, and elucidating why it arises from the perspective of statistical…