Web: http://arxiv.org/abs/2202.09275

Sept. 23, 2022, 1:12 a.m. | Vahid Partovi Nia, Alireza Ghaffari, Mahdi Zolnouri, Yvon Savaria

cs.LG updates on arXiv.org arxiv.org

Performance optimization of deep learning models is conducted either manually
or through automatic architecture search, or a combination of both. On the
other hand, their performance strongly depends on the target hardware and how
successfully the models were trained. We propose to use a multi-dimensional
Pareto frontier to re-define the efficiency measure of candidate deep learning
models, where several variables such as training cost, inference latency, and
accuracy play a relative role in defining a dominant model. Furthermore, a
random …

arxiv evaluation networks neural networks performance

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