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cs.NE updates on arXiv.org

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Reliable and Fast Recurrent Neural Network Architecture Optimization
Andrés Camero, Jamal Toutouh, Enrique Alba · 2021-06-29 · via cs.NE updates on arXiv.org

This article introduces Random Error Sampling-based Neuroevolution (RESN), a novel automatic method to optimize recurrent neural network architectures. RESN combines an evolutionary algorithm with a training-free evaluation approach. The results show that RESN achieves state-of-the-art error performance while reducing by half the computational time.

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