Results 1 to 10 of about 70,075 (156)
Auto-GNN: Neural architecture search of graph neural networks [PDF]
Frontiers in Big Data, 2022 Graph neural networks (GNNs) have been widely used in various graph analysis tasks. As the graph characteristics vary significantly in real-world systems, given a specific scenario, the architecture parameters need to be tuned carefully to identify a ...
Kaixiong Zhou +4 more
doaj +2 more sources
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
doaj +3 more sources
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
doaj +2 more sources
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
doaj +2 more sources
Advances in neural architecture search. [PDF]
Natl Sci RevABSTRACTAutomated machine learning (AutoML) has achieved remarkable success in automating the non-trivial process of designing machine learning models. Among the focal areas of AutoML, neural architecture search (NAS) stands out, aiming to systematically explore the complex architecture space to discover the optimal neural architecture configurations ...
Wang X, Zhu W.
europepmc +3 more sources
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
doaj +2 more sources
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
doaj +2 more sources
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
doaj +2 more sources
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
doaj +2 more sources
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
doaj +2 more sources