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Published in 2022 at "IEEE Transactions on Industrial Informatics"
DOI: 10.1109/tii.2022.3184700
Abstract: Differentiable neural architecture search (DARTS), as a gradient-guided search method, greatly reduces the cost of computation and speeds up the search. In DARTS, the architecture parameters are introduced to the candidate operations, but the parameters…
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Keywords:
differentiable neural;
architecture;
search;
attention ... See more keywords
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Published in 2021 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2021.3072950
Abstract: Recently, differentiable neural architecture search (NAS) methods have made significant progress in reducing the computational costs of NASs. Existing methods search for the best architecture by choosing candidate operations with higher architecture weights. However, architecture…
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Keywords:
differentiable neural;
operation importance;
architecture;
search ... See more keywords
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Published in 2024 at "IEEE Transactions on Neural Networks and Learning Systems"
DOI: 10.1109/tnnls.2024.3378697
Abstract: Approximation ability is one of the most important topics in the field of neural networks (NNs). Feedforward NNs, activated by rectified linear units and some of their specific smoothed versions, provide universal approximators to convex…
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Keywords:
modular differentiable;
differentiable neural;
abilities modular;
approximation abilities ... See more keywords
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Published in 2025 at "PLOS One"
DOI: 10.1371/journal.pone.0329480
Abstract: Image classification, as the core task of computer vision, has broad application value in fields such as medical diagnosis and intelligent transportation.However, the ability of differentiable neural architecture to search (NAS) for local information is…
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Keywords:
classification;
image classification;
neural architecture;
search ... See more keywords