  The self-consistent field (SCF) iteration, combined with its variants, is one
of the most widely used algorithms in quantum chemistry. We propose a procedure
to adapt the SCF iteration for the p-Laplacian eigenproblem, which is an
important problem in the field of unsupervised learning. We formulate the
p-Laplacian eigenproblem as a type of nonlinear eigenproblem with one
eigenvector nonlinearity , which then allows us to adapt the SCF iteration for
its solution after the application of suitable regularization techniques. The
results of our numerical experiments confirm the viablity of our approach.
