JCSS paper is out!

16 Nov 2017 • 1 min read
Tags:   news science

Our JCSS paper (“Robust optimization in the presence of uncertainty: A generic approach”) is out - a nice birthday present btw!

The highlights of the paper are:

  • A new approach to robust optimization in presence of uncertainty ROPU is proposed.
  • ROPU takes two typical instances and doesn’t assume any special noise model.
  • ROPU measures task specific similarity of instances, i.e., its input relevance.
  • The similarity measure detects if given instances are not similar or too noisy.
  • Instance similarity favors good localization (!) of solutions rather than costs.

Want to discuss anything? Comments are welcome via e-mail alexey@gronskiy.com, Telegram @agronskiy or any other social media.