Results 31 to 40 of about 7,839,223 (287)
One-Shot Neural architecture search via novelty driven sampling [PDF]
, 2020 One-Shot Neural architecture search (NAS) has received wide attentions due to its computational efficiency. Most state-of-the-art One-Shot NAS methods use the validation accuracy based on inheriting weights from the supernet as the stepping stone to ...
Zhang, Miao +14 more
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NAS-TasNet: Neural Architecture Search for Time-Domain Speech Separation
IEEE Access, 2022 The fully convolutional time-domain speech separation network (Conv-TasNet) has been used as a backbone model in various studies because of its structural excellence. To maximize the performance and efficiency of Conv-TasNet, we attempt to apply a neural
Joo-Hyun Lee +3 more
doaj +1 more source
DC-NAS: Divide-and-Conquer Neural Architecture Search
CoRR, 2020 Most applications demand high-performance deep neural architectures costing limited resources. Neural architecture searching is a way of automatically exploring optimal deep neural networks in a given huge search space. However, all sub-networks are usually evaluated using the same criterion; that is, early stopping on a small proportion of the ...
Yunhe Wang 0001, Yixing Xu, Dacheng Tao
openaire +3 more sources
Shapley-NAS: Discovering Operation Contribution for Neural Architecture Search
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022 Accepted to ...
Han Xiao 0010 +4 more
openaire +4 more sources
Applied Sciences, 2020 In this paper, we apply the neural architecture search (NAS) method to Korean grammaticality judgment tasks. Since the word order of a language is the final result of complex syntactic operations, a successful neural architecture search in linguistic ...
Kang-moon Park +2 more
doaj +1 more source
Novel Surrogate Measures Based on a Similarity Network for Neural Architecture Search
IEEE Access, 2023 We propose two novel surrogate measures to predict the validation accuracy of the classification produced by a given neural architecture, thus eliminating the need to train it, in order to speed up neural architecture search (NAS). The surrogate measures
Zeki Kus, Can Akkan, Ayla Gulcu
doaj +1 more source
Scientific Reports, 2021 The design of neural architecture to address the challenge of detecting abnormalities in histopathology images can leverage the gains made in the field of neural architecture search (NAS).
Olaide N. Oyelade, Absalom E. Ezugwu
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A hybrid neural architecture search for hyperspectral image classification
Frontiers in Physics, 2023 Convolution neural network (CNN)is widely used in hyperspectral image (HSI) classification. However, the network architecture of CNNs is usually designed manually, which requires careful fine-tuning.
Aili Wang +4 more
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DCP-NAS: Discrepant Child-Parent Neural Architecture Search for 1-bit CNNs [PDF]
, 2023 Neural architecture search (NAS) proves to be among the effective approaches for many tasks by generating an application-adaptive neural architecture, which is still challenged by high computational cost and memory consumption.
Li, Yanjing +6 more
core +1 more source
Applied Sciences, 2023 In the realm of machine learning, the optimization of hyperparameters and the design of neural architectures entail laborious and time-intensive endeavors.
Jiyong Shin, Kyongseok Park, Dae-Ki Kang
doaj +1 more source