Search Results for author:
Found 3 papers, 1 papers with code
Semi-Supervised Machine Learning: a Homological Approach
In this paper we describe the mathematical foundations of a new approach to semi-supervised Machine Learning.
Semi-Supervised Learning for Image Classification using Compact Networks in the BioMedical Context
By combining semi-supervised learning methods with compact networks, it is possible to obtain a similar performance to standard size networks.
A Topological Approach for Semi-Supervised Learning
In the former, we have used a homological approach that consists in studying the persistence diagrams associated with the data using the Bottleneck and Wasserstein distances.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
