4 ms·
Can confirm. I've played around with differential evolution and a few others. Nothing was able to beat CMA-ES. At best, after some manual tuning it was just bar
by Matumio 2y ago
Can confirm. I've played around with differential evolution and a few others. Nothing was able to beat CMA-ES. At best, after some manual tuning it was just barely matching the untuned CMA-ES. (The task was to optimize a small neural network, gradients not easily available.)
CMA-ES is not suited for very large problems (more than a few hundred parameters), but there are several variants that can handle this, like sep-CMA-ES.
- sevensor 2y agoDifferential evolution definitely comes in second as far as I’ve seen. In fact, what I’ve seen is that evolutionary search operators are effective inversely proportional to how faithfully they model actual biological processes.