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Gradient Descent Effects on Differential Neural Architecture Search: A Survey
IEEE Access, 2021 Gradient Descent, an effective way to search for the local minimum of a function, can minimize training and validation loss of neural architectures and also be incited in an appropriate order to decrease the searching cost of neural architecture search ...
Santanu Santra +2 more
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Heterogeneity-Aware Personalized Federated Neural Architecture Search [PDF]
EntropyFederated learning (FL), which enables collaborative learning across distributed nodes, confronts a significant heterogeneity challenge, primarily including resource heterogeneity induced by different hardware platforms, and statistical heterogeneity ...
An Yang, Ying Liu
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Neural architecture search applying optimal stopping theory [PDF]
Frontiers in Artificial IntelligenceNeural architecture search (NAS) exploration requires tremendous amounts of computational power to properly explore. This makes exploration of modern NAS search spaces impractical for researchers due to the infrastructure investments required and the ...
Matthew Sheehan, Oleg Yakimenko
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Population-based guiding for evolutionary neural architecture search [PDF]
Scientific ReportsNeural Architecture Search (NAS)—combined with biology-inspired evolutionary methods—can help discover suitable architectures tailored to a given objective.
Stefan Dendorfer, Andreas M. Kist
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Unveil Fundamental Graph Properties for Neural Architecture Search [PDF]
Advanced ScienceDeep learning profoundly impacts various areas, such as face recognition and language translation. Owing to the increasingly high computational costs of training neural architectures, it is intractable to manually examine the performance of various ...
Zhenhan Huang +4 more
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LiteGaze: Neural architecture search for efficient gaze estimation. [PDF]
PLoS ONE, 2023 Gaze estimation plays a critical role in human-centered vision applications such as human-computer interaction and virtual reality. Although significant progress has been made in automatic gaze estimation by deep convolutional neural networks, it is ...
Xinwei Guo +3 more
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Neural Architecture Search Survey: A Computer Vision Perspective [PDF]
Sensors, 2023 In recent years, deep learning (DL) has been widely studied using various methods across the globe, especially with respect to training methods and network structures, proving highly effective in a wide range of tasks and applications, including image ...
Jeon-Seong Kang +5 more
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Brain tumor classification based on neural architecture search [PDF]
Scientific Reports, 2022 Brain tumor is a life-threatening disease and causes about 0.25 million deaths worldwide in 2020. Magnetic Resonance Imaging (MRI) is frequently used for diagnosing brain tumors. In medically underdeveloped regions, physicians who can accurately diagnose
Shubham Chitnis +2 more
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Review of Research on Neural Architecture Search Algorithms Based on Non-Gradient Evolution [PDF]
Jisuanji gongcheng, 2020 Automated deep learning is one of the new research hotspots in the field of deep learning.Neural architecture search algorithms are frequently used for the implementation of automated deep learning,as they can automatically design neural network ...
SHANG Diya, SUN Hua, HONG Zhenhou, ZENG Qingliang
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Graph Neural Architecture Search: A Survey
Tsinghua Science and Technology, 2022 In academia and industries, graph neural networks (GNNs) have emerged as a powerful approach to graph data processing ranging from node classification and link prediction tasks to graph clustering tasks. GNN models are usually handcrafted.
Babatounde Moctard Oloulade +4 more
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