Semi-Supervised Machine Learning: a Homological Approach
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Abstract (arXiv)
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.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 0 of its 6 references that are in the map. First posted on arXiv 27 Jan 2023.
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