Tue, 30 May 2017
14:30
14:30
L5
New approaches for global optimization methods
Adilet Otemisov
(Mathematical Institute and Alan Turing Institute)
Abstract
We present some dimensionality reduction techniques for global optimization algorithms, in order to increase their scalability. Inspired by ideas in machine learning, and extending the approach of random projections in Zhang et al (2016), we present some new algorithmic approaches for global optimisation with theoretical guarantees of good behaviour and encouraging numerical results.