24 citations · 87 across the 20 of their papers we have counts for
5 papers · 1 filter
Consensus-based optimization for linearly separable functions
Christian Fiedler, Tim Roith
Consensus-based optimization (CBO) is an efficient metaheuristic for global optimisation with attractive mathematical properties, allowing global convergence results even in non-co…
Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies
Tim Roith, Leon Bungert, Philipp Wacker
Consensus-based optimization (CBO) has established itself as an efficient gradient-free optimization scheme, with attractive mathematical properties, such as mean-field convergence…
MirrorCBO: A consensus-based optimization method in the spirit of mirror descent
Leon Bungert, Franca Hoffmann, Dohyeon Kim +1
In this work we propose MirrorCBO, a consensus-based optimization (CBO) method which generalizes standard CBO in the same way that mirror descent generalizes gradient descent. For…
CBX: Python and Julia packages for consensus-based interacting particle methods
Rafael Bailo, Alethea Barbaro, Susana N. Gomes +4
We introduce CBXPy and ConsensusBasedX.jl, Python and Julia implementations of consensus-based interacting particle systems (CBX), which generalise consensus-based optimization met…
Polarized consensus-based dynamics for optimization and sampling
Leon Bungert, Tim Roith, Philipp Wacker
In this paper we propose polarized consensus-based dynamics in order to make consensus-based optimization (CBO) and sampling (CBS) applicable for objective functions with several g…