Matches in SemOpenAlex for { <https://semopenalex.org/work/W3007579076> ?p ?o ?g. }
Showing items 1 to 82 of
82
with 100 items per page.
- W3007579076 abstract "As deep neural networks have been deployed in more and more applications over the past half decade and are finding their way into an ever increasing number of operational systems, their energy consumption becomes a concern whether running in the datacenter or on edge devices. Hyperparameter optimization and automated network design for deep learning is a quickly growing field, but much of the focus has remained only on optimizing for the performance of the machine learning task. In this work, we demonstrate that the best performing networks created through this automated network design process have radically different computational characteristics (e.g. energy usage, model size, inference time), presenting the opportunity to utilize this optimization process to make deep learning networks more energy efficient and deployable to smaller devices. Optimizing for these computational characteristics is critical as the number of applications of deep learning continues to expand." @default.
- W3007579076 created "2020-03-06" @default.
- W3007579076 creator A5000241304 @default.
- W3007579076 creator A5021986280 @default.
- W3007579076 creator A5029444976 @default.
- W3007579076 creator A5029879538 @default.
- W3007579076 creator A5033784578 @default.
- W3007579076 creator A5041928659 @default.
- W3007579076 creator A5046319147 @default.
- W3007579076 creator A5070858681 @default.
- W3007579076 creator A5078825022 @default.
- W3007579076 date "2019-12-01" @default.
- W3007579076 modified "2023-09-27" @default.
- W3007579076 title "Evolving Energy Efficient Convolutional Neural Networks" @default.
- W3007579076 cites W1519432379 @default.
- W3007579076 cites W1604973310 @default.
- W3007579076 cites W2075863084 @default.
- W3007579076 cites W2117539524 @default.
- W3007579076 cites W2121775913 @default.
- W3007579076 cites W2156679542 @default.
- W3007579076 cites W2194775991 @default.
- W3007579076 cites W2250904038 @default.
- W3007579076 cites W2257979135 @default.
- W3007579076 cites W2580834719 @default.
- W3007579076 cites W2606722458 @default.
- W3007579076 cites W2767077319 @default.
- W3007579076 cites W2783525259 @default.
- W3007579076 cites W2963821229 @default.
- W3007579076 cites W2964024268 @default.
- W3007579076 cites W2964081807 @default.
- W3007579076 cites W2964217848 @default.
- W3007579076 cites W2965658867 @default.
- W3007579076 cites W2969335882 @default.
- W3007579076 cites W2955648404 @default.
- W3007579076 doi "https://doi.org/10.1109/bigdata47090.2019.9006239" @default.
- W3007579076 hasPublicationYear "2019" @default.
- W3007579076 type Work @default.
- W3007579076 sameAs 3007579076 @default.
- W3007579076 citedByCount "7" @default.
- W3007579076 countsByYear W30075790762020 @default.
- W3007579076 countsByYear W30075790762022 @default.
- W3007579076 crossrefType "proceedings-article" @default.
- W3007579076 hasAuthorship W3007579076A5000241304 @default.
- W3007579076 hasAuthorship W3007579076A5021986280 @default.
- W3007579076 hasAuthorship W3007579076A5029444976 @default.
- W3007579076 hasAuthorship W3007579076A5029879538 @default.
- W3007579076 hasAuthorship W3007579076A5033784578 @default.
- W3007579076 hasAuthorship W3007579076A5041928659 @default.
- W3007579076 hasAuthorship W3007579076A5046319147 @default.
- W3007579076 hasAuthorship W3007579076A5070858681 @default.
- W3007579076 hasAuthorship W3007579076A5078825022 @default.
- W3007579076 hasBestOaLocation W30075790762 @default.
- W3007579076 hasConcept C121332964 @default.
- W3007579076 hasConcept C154945302 @default.
- W3007579076 hasConcept C186370098 @default.
- W3007579076 hasConcept C41008148 @default.
- W3007579076 hasConcept C62520636 @default.
- W3007579076 hasConcept C81363708 @default.
- W3007579076 hasConceptScore W3007579076C121332964 @default.
- W3007579076 hasConceptScore W3007579076C154945302 @default.
- W3007579076 hasConceptScore W3007579076C186370098 @default.
- W3007579076 hasConceptScore W3007579076C41008148 @default.
- W3007579076 hasConceptScore W3007579076C62520636 @default.
- W3007579076 hasConceptScore W3007579076C81363708 @default.
- W3007579076 hasLocation W30075790761 @default.
- W3007579076 hasLocation W30075790762 @default.
- W3007579076 hasOpenAccess W3007579076 @default.
- W3007579076 hasPrimaryLocation W30075790761 @default.
- W3007579076 hasRelatedWork W2285788670 @default.
- W3007579076 hasRelatedWork W2521062615 @default.
- W3007579076 hasRelatedWork W2735477435 @default.
- W3007579076 hasRelatedWork W2946452775 @default.
- W3007579076 hasRelatedWork W2955938200 @default.
- W3007579076 hasRelatedWork W2998526951 @default.
- W3007579076 hasRelatedWork W3016958897 @default.
- W3007579076 hasRelatedWork W3090822330 @default.
- W3007579076 hasRelatedWork W3181746755 @default.
- W3007579076 hasRelatedWork W4239686595 @default.
- W3007579076 isParatext "false" @default.
- W3007579076 isRetracted "false" @default.
- W3007579076 magId "3007579076" @default.
- W3007579076 workType "article" @default.