57 citations · 148 across the 15 of their papers we have counts for
Showing 2023Show all
2 papers · 1 filter
math.OC2023★ 4 cited
Consensus-Based Optimization with Truncated Noise
Massimo Fornasier, Peter Richtárik, Konstantin Riedl +1
Consensus-based optimization (CBO) is a versatile multi-particle metaheuristic optimization method suitable for performing nonconvex and nonsmooth global optimizations in high dime…
cs.LG2023
Gradient is All You Need? How Consensus-Based Optimization can be Interpreted as a Stochastic Relaxation of Gradient Descent
Konstantin Riedl, Timo Klock, Carina Geldhauser +1
In this paper, we provide a novel analytical perspective on the theoretical understanding of gradient-based learning algorithms by interpreting consensus-based optimization (CBO),…