Manifold alignment

Manifold alignment is a technique in machine learning and computer vision that aims at aligning or matching data from different sources that may lie in different but related high-dimensional spaces, typically referred to as manifolds. The central idea is that even if the data comes from different distributions or domains, it can be meaningfully compared and aligned based on inherent geometric structures.