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NAS-Bench-Graph: Benchmarking Graph Neural Architecture Search
Advances in Neural Information Processing Systems 35, 2022 Graph neural architecture search (GraphNAS) has recently aroused considerable attention in both academia and industry. However, two key challenges seriously hinder the further research of GraphNAS. First, since there is no consensus for the experimental setting, the empirical results in different research papers are often not comparable and even not ...
Yijian Qin +4 more
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NAS-VAD: Neural Architecture Search for Voice Activity Detection
Interspeech 2022, 2022 Various neural network-based approaches have been proposed for more robust and accurate voice activity detection (VAD). Manual design of such neural architectures is an error-prone and time-consuming process, which prompted the development of neural architecture search (NAS) that automatically design and optimize network architectures.
Daniel Rho, Jinhyeok Park, Jong Hwan Ko
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Neural architecture search as sparse supernet
, 2021 This paper aims at enlarging the problem of Neural Architecture Search (NAS) from Single-Path and Multi-Path Search to automated Mixed-Path Search.
WU, Y. +8 more
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HyT-NAS: Hybrid Transformers Neural Architecture Search for Edge Devices [PDF]
, 2023 Vision Transformers have enabled recent attention-based Deep Learning (DL) architectures to achieve remarkable results in Computer Vision (CV) tasks.
Ouarnoughi, Hamza +3 more
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EAT-NAS: elastic architecture transfer for accelerating large-scale neural architecture search [PDF]
Science China Information Sciences, 2021 Neural architecture search (NAS) methods have been proposed to release human experts from tedious architecture engineering. However, most current methods are constrained in small-scale search due to the issue of computational resources. Meanwhile, directly applying architectures searched on small datasets to large datasets often bears no performance ...
Jiemin Fang +7 more
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Differentiable neural architecture search in equivalent space with exploration enhancement [PDF]
, 2023 Recent works on One-Shot Neural Architecture Search (NAS) mostly adopt a bilevel optimization scheme to alternatively optimize the supernet weights and architecture parameters after relaxing the discrete search space into a differentiable space. However,
Chang, X +5 more
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CommGNAS: Unsupervised Graph Neural Architecture Search for Community Detection [PDF]
, 2023 Graph neural architecture search (GNAS) has been successful in many supervised learning tasks, such as node classification, graph classification, and link prediction.
Raeed Al-Sabri +13 more
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Self-Supervised learning for Neural Architecture Search (NAS)
CoRR, 2023 17 pages, 11 ...
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GPT-NAS: Evolutionary Neural Architecture Search with the Generative Pre-Trained Model [PDF]
, 2023 Neural Architecture Search (NAS) has emerged as one of the effective methods to design the optimal neural network architecture automatically. Although neural architectures have achieved human-level performances in several tasks, few of them are obtained ...
Lv, Jiancheng +4 more
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Proceedings of the 1st Workshop on Machine Learning and Systems, 2021 $\mu$NAS is available at https://github.com/eliberis ...
Edgar Liberis +2 more
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