2 code implementations • 16 Jun 2023 • Konstantin Riedl, Timo Klock, Carina Geldhauser, Massimo Fornasier
The fundamental value of such link between CBO and SGD lies in the fact that CBO is provably globally convergent to global minimizers for ample classes of nonsmooth and nonconvex objective functions, hence, on the one side, offering a novel explanation for the success of stochastic relaxations of gradient descent.
3 code implementations • 22 Nov 2022 • Konstantin Riedl
In this paper we study consensus-based optimization (CBO), a versatile, flexible and customizable optimization method suitable for performing nonconvex and nonsmooth global optimizations in high dimensions.
