HOTNAS: Hierarchical Optimal Transport for Neural Architecture Search-Reference-Cited by-同舟云学术

HOTNAS: Hierarchical Optimal Transport for Neural Architecture Search

Published:2023-06 Issue: Volume: Page:
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Container-title:2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
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Author:

Yang Jiechao¹,Liu Yong¹,Xu Hongteng¹

Affiliation:

1. Gaoling School of Artificial Intelligence, Renmin University of China,Beijing,China

Funder

National Natural Science Foundation of China

Beijing Natural Science Foundation

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10203037/10203050/10205160.pdf?arnumber=10205160

Reference70 articles.

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2. TrajectoryNet: A dynamic optimal transport network for modeling cellular dynamics;tong;ICML,2020

3. Nats-bench: Benchmarking NAS algorithms for architecture topology and size;dong;IEEE Transactions on Pattern Analysis and Machine Intelligence,2022

4. Optimal transport for structured data with application on graphs;titouan;ICML,2019

5. TransNAS-Bench-101: Improving transferability and Generalizability of Cross-Task Neural Architecture Search

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