How consensus-based optimization can be interpreted as a stochastic relaxation of gradient descent
We provide a novel analytical perspective on the theoretical understanding of gradient-based learning algorithms by interpreting consensus-based optimization (CBO), a recently proposed multi-particle derivative-free optimization method, as a stochastic relaxation of gradient descent. Remarkably, we...
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| Fformat: | Conference item |
| Iaith: | English |
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OpenReview
2024
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