AutoML.org

Freiburg-Hannover-Tübingen

Literature on Neural Architecture Search

Maintained by Difan Deng and Marius Lindauer.

The following list considers papers related to neural architecture search. It is by no means complete. If you miss a paper on the list, please let us know.

Please note that although NAS methods steadily improve, the quality of empirical evaluations in this field are still lagging behind compared to other areas in machine learning, AI and optimization. We would therefore like to share some best practices for empirical evaluations of NAS methods, which we believe will facilitate sustained and measurable progress in the field. If you are interested in a teaser, please read our blog post or directly jump to our checklist.

Transformers have gained increasing popularity in different domains. For a comprehensive list of papers focusing on Neural Architecture Search for Transformer-Based spaces, the awesome-transformer-search repo is all you need.


2755 entries « 56 of 56 »

0000

5.

Cho, Minsu

Deep Learning Model Design Algorithms for High-Performing Plaintext and Ciphertext Inference PhD Thesis

0000.

Links | BibTeX

4.

Zhou, Dongzhan

Designing Deep Model and Training Paradigm for Object Perception PhD Thesis

0000.

Links | BibTeX

3.

Shariatzadeh, Seyed Mahdi; Fathy, Mahmood; Berangi, Reza

Improving the accuracy and speed of fast template-matching algorithms by neural architecture search Journal Article

In: Expert Systems, vol. n/a, no. n/a, pp. e13358, 0000.

Abstract | Links | BibTeX

2.

Yang, Yongjia; Zhan, Jinyu; Jiang, Wei; Jiang, Yucheng; Yu, Antai

Neural architecture search for resource constrained hardware devices: A survey Journal Article

In: IET Cyber-Physical Systems: Theory & Applications, vol. n/a, no. n/a, 0000.

Abstract | Links | BibTeX

1.

Yan, Longhao; Wu, Qingyu; Li, Xi; Xie, Chenchen; Zhou, Xilin; Li, Yuqi; Shi, Daijing; Yu, Lianfeng; Zhang, Teng; Tao, Yaoyu; Yan, Bonan; Zhong, Min; Song, Zhitang; Yang, Yuchao; Huang, Ru

Neural Architecture Search with In-Memory Multiply–Accumulate and In-Memory Rank Based on Coating Layer Optimized C-Doped Ge2Sb2Te5 Phase Change Memory Journal Article

In: Advanced Functional Materials, vol. n/a, no. n/a, pp. 2300458, 0000.

Abstract | Links | BibTeX

2755 entries « 56 of 56 »