Schroedinger Eigenmaps for the Analysis of Bio-Medical Data

Computer Science – Computational Engineering – Finance – and Science

Scientific paper

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Scientific paper

We introduce Schroedinger Eigenmaps, a new semi-supervised manifold learning
and recovery technique. This method is based on an implementation of graph
Schroedinger operators with appropriately constructed barrier potentials as
carriers of labeled information. We apply it to analyze two complex bio-medical
datasets: multispectral retinal images and microarray gene expressions.

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