Stable Blanket with Hidden Variables and Cycles
Stabilized regression aims to identify a set of predictors whose conditional relationship with a response variable remains invariant across different environments. Existing graphical characterizations of the stable blanket are mainly developed for structural causal models (SCMs) without hidden variables or causal cycles. However, latent variables and feedback relationships naturally arise in many applications, and they can change both the Markov blanket and the set of predictors that remain stable under interventions. This paper studies stable blankets in graphical causal models with hidden variables, causal cycles, and both features simultaneously. For models with hidden variables, we us...
| Authors | Hanqing Xiang |
|---|---|
| Primary category | stat.ML |
| Published | 3 May 2026 |
| Last updated at source | 3 May 2026 |
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