这篇用范畴论重讲统计学习模型，少见。适合数学背景的人看，能帮你找到跟机器学习研究接头的入口。
这篇 arXiv 2608.03706 论文面向统计学习初学者，梳理了经典统计学习模型与常见算法。作者用范畴论语言重新描述这些模型，尝试为它们提供统一的构造视角。文章目标是吸引基础数学等领域的研究者参与统计学习相关课题。
To Describe or Construct Statistical Learning Models Using the Category-theoretical Language
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.