  Unsupervised clustering of scattered, noisy and high-dimensional data points
is an important and difficult problem. Tight continuous relaxations of balanced
cut problems have recently been shown to provide excellent clustering results.
In this paper, we present an explicit-implicit gradient flow scheme for the
relaxed ratio cut problem, and prove that the algorithm converges to a critical
point of the energy. We also show the efficiency of the proposed algorithm on
the two moons dataset.
