arXiv Open Access 2025

From Formal Language Theory to Statistical Learning: Finite Observability of Subregular Languages

Katsuhiko Hayashi Hidetaka Kamigaito
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Abstrak

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. These results demonstrate that the subregular hierarchy provides a rigorous and interpretable foundation for modeling natural language structure. Our code used in real-data experiments is available at https://github.com/UTokyo-HayashiLab/subregular.

Topik & Kata Kunci

Penulis (2)

K

Katsuhiko Hayashi

H

Hidetaka Kamigaito

Format Sitasi

Hayashi, K., Kamigaito, H. (2025). From Formal Language Theory to Statistical Learning: Finite Observability of Subregular Languages. https://arxiv.org/abs/2509.22598

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Informasi Jurnal
Tahun Terbit
2025
Bahasa
en
Sumber Database
arXiv
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Open Access ✓