Ensembles Methods for Optimisation Workshop

gecco_logo_HQ

Ensemble Methods for Optimisation

Workshop @ GECCO 2017, Berlin

Organisers: Emma Hart and Kevin Sim

In the field of machine-learning, ensemble-methods that combine decisions from multiple learning algorithms to make accurate predictions have been the focus of intense research for well over a decade, with a broad range of empirical results underpinned by a sound theoretical understanding. Ensemble methods have also found favour within the constraint satisfaction and satisfiability domains where they are commonly referred to as portfolio methods. In the latter case, portfolios tend to be composed from exact solvers, and are evaluated according to run-time metrics.

On the other hand, research in ensemble-methods using meta-heuristic algorithms – in which solution quality rather than run-time is the driving factor – lags behind machine-learning and satisfiability research in both theory and practice. Many fundamental questions remain with respect to how to construct, and design ensembles that will be addressed during the workshop:

  • How should we select algorithms to form an ensemble?
  • How large should the selection pool be – and where do we find algorithms to form the pool?
  • Are automated algorithm generation techniques required to design new algorithms to provide a large enough pool?
  • Machine-learning theory suggests that diversity between components is a key factor – what diversity measures can be used to successfully distinguish between meta-heuristic algorithms?
  • How should the ensemble operate? Algorithms might collaborate, i.e. the computational budget is divided between algorithms within the ensemble, or cooperate, in that different algorithms solve different instances?
  • What domains are ensemble methods best suited to?
Submissions
We invite paper submissions describing technical work as well as conceptual/visionary short papers. Demos accompanied by short papers are also welcomed. The workshop encourages presentation of work in early stages in order to encourage discussion amongst participants.
Technical papers have a limit of 8 pages.
Conceptual and Demo papers have a limit of 2 pages.
Submissions should be emailed to e DOT hart AT napier.ac.uk with the subject heading:
EfO Submission
All papers should be in ACM (Association for Computing Machinery)
format. Please see GECCO 2017 http://gecco-2017.sigevo.org for
details. Papers should not be anonymised. All papers should be
submitted in PDF format.
All accepted papers will be presented at GI-2017 and will appear in
the GECCO workshop volume.
Key Dates
Paper submission deadline:  March 29, 2017 (no extensions permitted)