AI RESEARCH
From Formal Language Theory to Statistical Learning: Finite Observability of Subregular Languages
arXiv CS.LG
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ArXi:2509.22598v2 Announce Type: replace-cross We prove that all standard subregular language classes are linearly separable when represented by their deciding predicates. This establishes finite observability and guarantees learnability with simple linear models. Synthetic experiments confirm perfect separability under noise-free conditions, while real-data experiments on English morphology show that learned features align with well-known linguistic constraints.