Stochastic Local Search for Pattern Set Mining
  Local search methods can quickly find good quality solutions in cases where
systematic search methods might take a large amount of time. Moreover, in the
context of pattern set mining, exhaustive search methods are not applicable due
to the large search space they have to explore. In this paper, we propose the
application of stochastic local search to solve the pattern set mining.
Specifically, to the task of concept learning. We applied a number of local
search algorithms on a standard benchmark instances for pattern set mining and
the results show the potentials for further exploration.
