Papers/2608.20428
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Approximate Homomorphisms and Convergent Representations in Transducers

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transducersstochastic processesneural networksapproximate homomorphisms
2608.20428
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2h ago

Abstract

The paper investigates the stability of minimal representations of controlled stochastic processes, particularly transducers, under perturbations.

Reality Card

Core Claim

The study proves that minimal linear transducers implementing interfaces close to a finite-rank interface have an approximate homomorphism to the minimal implementation of that interface, with error linear in the perturbation size.

Method / Result

For every finite-rank interface, all minimal linear transducers have an approximate homomorphism with error linear in the perturbation size.

Limitations

The results depend on mild hypotheses regarding the indistinguishability of belief states, which may limit generalizability.

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