Tunhou Zhang — accepted AI-conference papers

2023

LISSNAS: Locality-based Iterative Search Space Shrinkage for Neural Architecture Search

Bhavna Gopal, Arjun Sridhar, Tunhou Zhang, Yiran Chen

IJCAI 2023poster

Search spaces hallmark the advancement of Neural Architecture Search (NAS). Large and complex search spaces with versatile building operators and structures provide more opportunities to brew promising architectures, yet pose severe challenges on efficient exploration and exploitation. Subsequently,…

Cited by 6 Source ↗PDF ↗Scholar ↗

2021

NASGEM: Neural Architecture Search via Graph Embedding Method

Hsin-Pai Cheng, Tunhou Zhang, Yixing Zhang, Shiyu Li, Feng Liang, Feng Yan +4

AAAI 2021technical

Neural Architecture Search (NAS) automates and prospers the design of neural networks. Estimator-based NAS has been proposed recently to model the relationship between architectures and their performance to enable scalable and flexible search. However, existing estimator-based methods encode the arc…

Cited by 24 Source ↗PDF ↗Scholar ↗