AttentiveNAS: Improving Neural Architecture Search via Attentive Sampling

Research article (2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021) · cited 89× · AI/ML
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AttentiveNAS: Improving Neural Architecture Search via Attentive Sampling

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AttentiveNAS: Improving Neural Architecture Search via Attentive Sampling is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). AttentiveNAS: Improving Neural Architecture Search via Attentive Sampling. Retrieved May 24, 2026, from https://4ort.xyz/entity/attentivenas-improving-neural-architecture-search-via-attentive-sampling
MLA “AttentiveNAS: Improving Neural Architecture Search via Attentive Sampling.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/attentivenas-improving-neural-architecture-search-via-attentive-sampling.
BibTeX @misc{4ortxyz_attentivenas-improving-neural-architecture-search-via-attentive-sampling_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{AttentiveNAS: Improving Neural Architecture Search via Attentive Sampling}}, year = {2026}, url = {https://4ort.xyz/entity/attentivenas-improving-neural-architecture-search-via-attentive-sampling}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): AttentiveNAS: Improving Neural Architecture Search via Attentive Sampling — https://4ort.xyz/entity/attentivenas-improving-neural-architecture-search-via-attentive-sampling (retrieved 2026-05-24)

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