Conditional computational barrier exists for learning k=1 invariant subspaces in samplable multi-environment instances under sparse recovery hardness; minimax risk is Theta(k(d-k)/(n|E|)) with phase transition at n* ~ k(d-k)/(|E| gamma^2).
A solution to co-occurrence bias in pedestrian attribute recognition: Theory, algorithms, and improvements
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Is Spurious Correlation Removal Always Learnable?
Conditional computational barrier exists for learning k=1 invariant subspaces in samplable multi-environment instances under sparse recovery hardness; minimax risk is Theta(k(d-k)/(n|E|)) with phase transition at n* ~ k(d-k)/(|E| gamma^2).