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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 35 / No. 12: AAAI-21 Technical Tracks 12

Rethinking Bi-Level Optimization in Neural Architecture Search: A Gibbs Sampling Perspective

February 1, 2023

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Abstract:

One-Shot architecture search, which aims to explore all possible operations jointly based on a single model, has been an active direction of Neural Architecture Search (NAS). As a well-known one-shot solution, Differentiable Architecture Search (DARTS) performs continuous relaxation on the architecture's importance and results in a bi-level optimization problem. However, as many recent studies have shown, DARTS cannot always work robustly for new tasks, which is mainly due to the approximate solution of the bi-level optimization. In this paper, one-shot neural architecture search is addressed by adopting a directed probabilistic graphical model to represent the joint probability distribution over data and model. Then, neural architectures are searched for and optimized by Gibbs sampling. We rethink the bi-level optimization problem as the task of Gibbs sampling from the posterior distribution, which expresses the preferences for different models given the observed dataset. We evaluate our proposed NAS method -- GibbsNAS on the search space used in DARTS/ENAS and the search space of NAS-Bench-201. Experimental results on multiple search space show the efficacy and stability of our approach.

Authors

Chao Xue

IBM Research


Xiaoxing Wang

Shanghai Jiao Tong University


Junchi Yan

Shanghai Jiao Tong University


Yonggang Hu

IBM System


Xiaokang Yang

Shanghai Jiao Tong University


Kewei Sun

IBM Research


DOI:

10.1609/aaai.v35i12.17262


Topics: AAAI

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HOW TO CITE:

Chao Xue||Xiaoxing Wang||Junchi Yan||Yonggang Hu||Xiaokang Yang||Kewei Sun Rethinking Bi-Level Optimization in Neural Architecture Search: A Gibbs Sampling Perspective Proceedings of the AAAI Conference on Artificial Intelligence, 35 (2021) 10551-10559.

Chao Xue||Xiaoxing Wang||Junchi Yan||Yonggang Hu||Xiaokang Yang||Kewei Sun Rethinking Bi-Level Optimization in Neural Architecture Search: A Gibbs Sampling Perspective AAAI 2021, 10551-10559.

Chao Xue||Xiaoxing Wang||Junchi Yan||Yonggang Hu||Xiaokang Yang||Kewei Sun (2021). Rethinking Bi-Level Optimization in Neural Architecture Search: A Gibbs Sampling Perspective. Proceedings of the AAAI Conference on Artificial Intelligence, 35, 10551-10559.

Chao Xue||Xiaoxing Wang||Junchi Yan||Yonggang Hu||Xiaokang Yang||Kewei Sun. Rethinking Bi-Level Optimization in Neural Architecture Search: A Gibbs Sampling Perspective. Proceedings of the AAAI Conference on Artificial Intelligence, 35 2021 p.10551-10559.

Chao Xue||Xiaoxing Wang||Junchi Yan||Yonggang Hu||Xiaokang Yang||Kewei Sun. 2021. Rethinking Bi-Level Optimization in Neural Architecture Search: A Gibbs Sampling Perspective. "Proceedings of the AAAI Conference on Artificial Intelligence, 35". 10551-10559.

Chao Xue||Xiaoxing Wang||Junchi Yan||Yonggang Hu||Xiaokang Yang||Kewei Sun. (2021) "Rethinking Bi-Level Optimization in Neural Architecture Search: A Gibbs Sampling Perspective", Proceedings of the AAAI Conference on Artificial Intelligence, 35, p.10551-10559

Chao Xue||Xiaoxing Wang||Junchi Yan||Yonggang Hu||Xiaokang Yang||Kewei Sun, "Rethinking Bi-Level Optimization in Neural Architecture Search: A Gibbs Sampling Perspective", AAAI, p.10551-10559, 2021.

Chao Xue||Xiaoxing Wang||Junchi Yan||Yonggang Hu||Xiaokang Yang||Kewei Sun. "Rethinking Bi-Level Optimization in Neural Architecture Search: A Gibbs Sampling Perspective". Proceedings of the AAAI Conference on Artificial Intelligence, 35, 2021, p.10551-10559.

Chao Xue||Xiaoxing Wang||Junchi Yan||Yonggang Hu||Xiaokang Yang||Kewei Sun. "Rethinking Bi-Level Optimization in Neural Architecture Search: A Gibbs Sampling Perspective". Proceedings of the AAAI Conference on Artificial Intelligence, 35, (2021): 10551-10559.

Chao Xue||Xiaoxing Wang||Junchi Yan||Yonggang Hu||Xiaokang Yang||Kewei Sun. Rethinking Bi-Level Optimization in Neural Architecture Search: A Gibbs Sampling Perspective. AAAI[Internet]. 2021[cited 2023]; 10551-10559.


ISSN: 2374-3468


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