Single-Domain Generalized Predictor for Neural Architecture Search System-Reference-Cited by-同舟云学术

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Single-Domain Generalized Predictor for Neural Architecture Search System

Published:2024-05 Issue:5 Volume:73 Page:1400-1413
ISSN:0018-9340
Container-title:IEEE Transactions on Computers
language:
Short-container-title:IEEE Trans. Comput.

Author:

Ma Lianbo¹^ORCID,Kang Haidong¹^ORCID,Yu Guo²^ORCID,Li Qing³^ORCID,He Qiang⁴^ORCID

Affiliation:

1. College of Software, Northeastern University, Shenyang, Liaoning, China

2. Nanjing Tech University, Nanjing, Jiangsu, China

3. Peng Cheng Laboratory, Shenzhen, Guangdong, China

4. College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, Liaoning, China

Funder

National Key R&D Program of China

NSFC Key Supported Project of the Major Research Plan

Key Technologies R&D Program of Liaoning Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/12/10494819/10438213.pdf?arnumber=10438213

Reference56 articles.

1. AtomNAS: Fine-grained end-to-end neural architecture search;Mei,2019

2. A Comprehensive Survey of Neural Architecture Search

3. Survey on Evolutionary Deep Learning: Principles, Algorithms, Applications, and Open Issues

4. Efficient neural architecture search via parameters sharing;Pham,2018

5. Understanding and simplifying one-shot architecture search;Bender,2018

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