Discrete approach to machine learning

Dmitriy Kashitsyn; Dmitriy Shabanov

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arXiv · 2508.00869

Discrete approach to machine learning

Dmitriy Kashitsyn·Dmitriy Shabanov

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Abstract

The article explores an encoding and structural information processing approach using sparse bit vectors and fixed-length linear vectors. The following are presented: a discrete method of speculative stochastic dimensionality reduction of multidimensional code and linear spaces with linear asymptotic complexity; a geometric method for obtaining discrete embeddings of an organised code space that reflect the internal structure of a given modality. The structure and properties of a code space are investigated using three modalities as examples: morphology of Russian and English languages, and immunohistochemical markers. Parallels are drawn between the resulting map of the code space layout and so-called pinwheels appearing on the mammalian neocortex. A cautious assumption is made about similarities between neocortex organisation and processes happening in our models.

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Dmitriy Kashitsyn, Dmitriy Shabanov. 2025-07-19. Discrete approach to machine learning. https://arxiv.org/abs/2508.00869

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