PPSN 2018 Workshop:

Investigating Optimization Problems from Machine Learning and Data Analysis

Overview

In continuous black-box optimization, there are a number of benchmark problem sets and competitions. However, the focus has mainly been on the performance and comparison of algorithms on artificial problems. The aim of this workshop is to instead make a set of optimization problems the center of focus, bringing together researchers to discuss and develop deeper insights into the structure and difficulty of the problem set, as well as experimental methodology (including algorithms). Several problem classes (and specific problem instances) from the area of machine learning and data analysis will be proposed in advance of the workshop submission deadline. Participants will be invited to submit a brief paper that shows new insights into the problems, for example via exploratory landscape analysis, algorithm performance (with a focus on "why") or analysis of the quality/diversity of solutions present in the problem instances.

Problem Set

A set of (approximately 10) specific problem instances will be provided in advance of the workshop. Likely problems include:

  • Clustering
  • Neural network training
  • Dimensionality reduction

Further details coming soon.

Submission

Details coming soon.

Location and Dates

The workshop will be held as part of the 15th International Conference on Parallel Problem Solving from Nature (PPSN 2018), Coimbra, Portugal. It will be a half-day workshop, to be scheduled on either the 8th or 9th of September, 2018. PPSN runs from 8-12th September, 2018.

Organizers

Marcus Gallagher, University of Queensland

Mike Preuss, University of Munster

Pascal Kerschke, University of Munster