Invention Application
- Patent Title: NEURAL ARCHITECTURE SEARCH FOR CONVOLUTIONAL NEURAL NETWORKS
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Application No.: US16674801Application Date: 2019-11-05
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Publication No.: US20200065689A1Publication Date: 2020-02-27
- Inventor: Vijay Vasudevan , Barret Zoph , Jonathon Shlens , Quoc V. Le
- Applicant: Google LLC
- Main IPC: G06N5/04
- IPC: G06N5/04 ; G06N3/04 ; G06N3/08 ; G06T7/00

Abstract:
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for determining neural network architectures. One of the methods includes generating, using a controller neural network having controller parameters and in accordance with current values of the controller parameters, a batch of output sequences. The method includes, for each output sequence in the batch: generating an instance of a child convolutional neural network (CNN) that includes multiple instances of a first convolutional cell having an architecture defined by the output sequence; training the instance of the child CNN to perform an image processing task; and evaluating a performance of the trained instance of the child CNN on the task to determine a performance metric for the trained instance of the child CNN; and using the performance metrics for the trained instances of the child CNN to adjust current values of the controller parameters of the controller neural network.
Public/Granted literature
- US11651259B2 Neural architecture search for convolutional neural networks Public/Granted day:2023-05-16
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