GPT-NAS: Neural Architecture Search Meets Generative Pre-Trained Transformer Model

GPT-NAS: Neural Architecture Search Meets Generative Pre-Trained Transformer Model

The pursuit of optimal neural network architectures is foundational to the progression of Neural Architecture Search (NAS). However, the existing NAS methods suffer from the following problem using traditional search strategies, i.e., when facing a large and complex search space, it is difficult to...

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Bibliographic Details
Main Authors: Caiyang Yu, Xianggen Liu, Yifan Wang, Yun Liu, Wentao Feng, Xiong Deng, Chenwei Tang, Jiancheng Lv
Format: Article
Language:English
Published: Tsinghua University Press 2025-02-01
Series:Big Data Mining and Analytics
Subjects:
neural architecture search (nas)
generative pre-trained transformer (gpt) model
evolutionary algorithm
image classification
Online Access:https://www.sciopen.com/article/10.26599/BDMA.2024.9020036
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https://www.sciopen.com/article/10.26599/BDMA.2024.9020036

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