  High-dimensional k-sample comparison is a common applied problem. We
construct a class of easy-to-implement nonparametric distribution-free tests
based on new tools and unexplored connections with spectral graph theory. The
test is shown to possess various desirable properties along with a
characteristic exploratory flavor that has practical consequences. The
numerical examples show that our method works surprisingly well under a broad
range of realistic situations.
