To Describe or Construct Statistical Learning Models Using the Category-theoretical Language

Congwei Song

To Describe or Construct Statistical Learning Models Using the Category-theoretical Language

Machine Learning 2026-08-04 v1

Authors: Congwei Song

Abstract

Statistical learning is a fascinating field that has long been the mainstream of machine learning/artificial intelligence. A large number of results have been produced which can be widely applied to real-world problems. It also leads to many research topics and also stimulates new research. This report summarizes some classical statistical learning models and well-known algorithms, especially for amateurs, and provides a category-theoretic perspective on understanding statistical learning models. The aim is to attract researchers from other fields, including basic mathematics, to participate in the research related to statistical learning.

Cite

@article{arxiv.2608.03706,
  title  = {To Describe or Construct Statistical Learning Models Using the Category-theoretical Language},
  author = {Congwei Song},
  journal= {arXiv preprint arXiv:2608.03706},
  year   = {2026}
}