Patent
Optimizing neural network architectures
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The article was published on 2019-10-22. It has received 5 citations till now. The article focuses on the topics: Artificial neural network.read more
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Patent
Anti-interference signal identification method and device, computer equipment and storage medium
Ma Yu,Wang Shafei,Fang Shanyao,Bao Yanfei,Yang Jian,Tian Zhen,Xiao Qingzheng,Liu Jie,Zhu Yuxuan +8 more
TL;DR: In this article, an anti-interference signal identification method and device, computer equipment and a storage medium are described. And each neural network corresponds to one label, so that each network can accurately predict shielded parts of the signal instances with the same label, while the shielded parts with other labels are difficult to predict.
Patent
Automated neural network generation using fitness estimation
Tyler McDonnell,Greenwood Bryson +1 more
TL;DR: In this paper, a matrix representation of a particular neural network is provided as input to a relative fitness estimator that is trained to generate estimated fitness data for neural networks of the population.
Patent
Image classification, generation and application of neural networks
Fielding Ben,Buchanan Will +1 more
TL;DR: In this paper, a method for generating and training neural networks for application in numerous fields including object or event recognition in images including visual sequences is presented, which is a computerized method of generating a neural network (NN), comprising generating successive candidate NNs (310, 545) using an optimisation algorithm (530), each NN having a number of connected blocks of layers (205), the layers having a plurality of neurons with connections having associated weights Each block comprises fixed and variable architectural parameters (210X, 210Y), the or each variable architectural parameter being determined by an
Patent
Neural network construction method, image processing method and devices
Xin Chen,Xie Lingxi,Tian Qi +2 more
TL;DR: In this article, a neural network construction method consisting of determining a search space and a plurality of construction units is presented, where the search network is used for neural architecture search and the architecture of the construction units within the search space is optimized to obtain optimized construction units.
Patent
Selective training of deep learning modules
TL;DR: In this article, a neural network is decomposed into a plurality of modules and tracks the training process module-by-module and datum-bydatum, recording auxiliary information during one iteration for retrieval during a later iteration.
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Neural Architecture Search with Reinforcement Learning
Barret Zoph,Quoc V. Le +1 more
TL;DR: This paper uses a recurrent network to generate the model descriptions of neural networks and trains this RNN with reinforcement learning to maximize the expected accuracy of the generated architectures on a validation set.
Patent
Method for simultaneously optimizing artificial neural network inputs and architectures using genetic algorithms
TL;DR: In this paper, a genetic algorithm is used to optimize ANN architectures and input spaces simultaneously, with a single genetic population simultaneously performing both phases of optimization, which allows for a very efficient ANN construction process with minimal user intervention.