Machine Learning Methods for Identifying Features of Global Optimization Problems in the Non-Stationary Environment and for Automatic Adaptation of Evolutionary and Bio-Inspired Algorithms
Funded by: FWF
- Siberian State University of Science and Technology
Most optimization and machine learning tasks are modeled in a stationary fashion. This means that the optimization or modeling objective does not change during an algorithm run. This international FWF project is concerned with advancing into the non-stationary domain using various methodological approaches.