Paper ID: 2301.11658

Semi-Supervised Machine Learning: a Homological Approach

Adrián Inés, César Domínguez, Jónathan Heras, Gadea Mata, Julio Rubio

In this paper we describe the mathematical foundations of a new approach to semi-supervised Machine Learning. Using techniques of Symbolic Computation and Computer Algebra, we apply the concept of persistent homology to obtain a new semi-supervised learning method.

Submitted: Jan 27, 2023