Manifold clustering is an important problem in motion and video segmentation, natural image clustering, and other applications where high-dimensional data lie on multiple, low-dimensional, nonlinear manifolds.

However, it may not be available in practice.

Districting is a complex combinatorial problem that consists in partitioning a geographical area into small districts.

Machine learning (ML) algorithms can often differ in performance across domains.