Discrete neural nets and polymorphic learning

Charlotte Aten

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arXiv · 2308.00677

Discrete neural nets and polymorphic learning

Charlotte Aten

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Abstract

Theorems from universal algebra such as that of Murski\u{i} from the 1970s have a striking similarity to universal approximation results for neural nets along the lines of Cybenko's from the 1980s. We consider here a discrete analogue of the classical notion of a neural net which places these results in a unified setting. We introduce a learning algorithm based on polymorphisms of relational structures and show how to use it for a classical learning task.

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Charlotte Aten. 2023-07-29. Discrete neural nets and polymorphic learning. https://arxiv.org/abs/2308.00677

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