In prediction-intervention games, stable-blanket predictors are at least as good as causal-parent predictors for two classes of follower objectives and can be worst-case optimal under additional conditions.
Maximum Risk Minimization with Random Forests.arXiv e-prints (2512.10445)
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
stat.ML 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Anchor PCA recovers a maximal invariant subspace for multi-domain data via PCA on a modified target matrix that trades off explained variance with domain agreement.
citing papers explorer
-
Prediction-Intervention Games and Invariant Sets
In prediction-intervention games, stable-blanket predictors are at least as good as causal-parent predictors for two classes of follower objectives and can be worst-case optimal under additional conditions.
-
Anchor PCA
Anchor PCA recovers a maximal invariant subspace for multi-domain data via PCA on a modified target matrix that trades off explained variance with domain agreement.