How powerful are performance predictors in neural architecture search?

C White, A Zela, R Ru, Y Liu… - Advances in Neural …, 2021 - proceedings.neurips.cc
Early methods in the rapidly develo** field of neural architecture search (NAS) required
fully training thousands of neural networks. To reduce this extreme computational cost …

Best practices for scientific research on neural architecture search

M Lindauer, F Hutter - Journal of Machine Learning Research, 2020 - jmlr.org
Finding a well-performing architecture is often tedious for both deep learning practitioners
and researchers, leading to tremendous interest in the automation of this task by means of …

Poster: Scaling up deep neural network optimization for edge inference

B Lu, J Yang, S Ren - 2020 IEEE/ACM Symposium on Edge …, 2020 - ieeexplore.ieee.org
Deep neural networks (DNNs) have been increasingly deployed on and integrated with
edge devices, such as mobile phones, drones, robots and wearables. Compared to cloud …

Scaling up deep neural network optimization for edge inference

B Lu, J Yang, S Ren - arxiv preprint arxiv:2009.00278, 2020 - arxiv.org
Deep neural networks (DNNs) have been increasingly deployed on and integrated with
edge devices, such as mobile phones, drones, robots and wearables. To run DNN inference …

Improving Neural Architecture Search With Bayesian Optimization and Generalization Mechanisms

VF Lopes - 2024 - search.proquest.com
Os avanços nos domínios da Inteligência Artificial (IA) e da Aprendizagem Automática (AA)
permitiram obter resultados impressionantes em vários problemas. Estes avanços podem …