Training sample data acquisition method, training sample data processing method, device and system

A technology of training samples and data, applied in the field of communication, can solve problems such as not considering the importance of model training, and achieve the effect of excellent model performance and high compression rate

Pending Publication Date: 2021-07-16
北京超星未来科技有限公司
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  • Description
  • Claims
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Problems solved by technology

Related edge computing technology mainly studies how to improve channel utilization, maximize communication capacity, and red

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  • Training sample data acquisition method, training sample data processing method, device and system
  • Training sample data acquisition method, training sample data processing method, device and system
  • Training sample data acquisition method, training sample data processing method, device and system

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[0031] Next, the technical solutions in the present specification are clearly, integrated, as clearly, as described herein are merely, not all of the embodiments of the present invention. Based on the embodiments of the present invention, those of ordinary skill in the art will belong to the scope of the present invention without paying in the premise of creative labor.

[0032] It should be noted that the terms "comprising" and "having" and "having" and any deformed in the present specification are intended to cover the included contained. For example, a series of steps or units comprising a series of steps or units are not limited to the listed steps or units, but alternatively include the steps or units not listed, or optionally also include For these processes, other steps or units inherent in the method, product, or equipment.

[0033] The present specification example discloses a method, processing method, apparatus, and system for training sample data. Detailed description w...

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Abstract

The invention discloses a training sample data obtaining method, a training sample data processing method, a device and a system. The data obtaining method suitable for being executed on an edge computing server comprises the steps: training a target model according to a current training set, and based on the current target model, obtaining a current importance calculation model for evaluating the importance of the data samples to the current target model, and calculating an importance evaluation value for each data sample in the test set through the current importance calculation model to obtain an importance mean value Lave; sending the parameters of the current importance calculation model and the importance mean value Lave to each edge device in a broadcast mode; calculating the access probability of each device according to the received access opportunity parameter value of each edge device, and sending a transmission trigger command to the edge device with the maximum access probability; and receiving data sent by the edge device after screening according to the current importance calculation model and the importance mean value Lave, and adding the data into the current training set to update the target model parameters.

Description

technical field [0001] The present invention relates to the field of communication technologies, and in particular, to a training sample data acquisition method, processing method, device and system. Background technique [0002] With the development of technologies such as the Internet of Things and the Internet of Vehicles and the deployment of large-scale intelligent terminals, edge computing is playing an increasingly important role in processing large amounts of data generated by terminals. For equipment deployment, resource allocation, and performance optimization in edge computing Research is also increasing. Related research starts from various aspects to optimize the communication performance of edge computing or combine edge computing methods into practical applications. The related edge computing technology mainly studies how to improve channel utilization, maximize communication capacity, and reduce delay through resource allocation, but does not consider the im...

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Application Information

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IPC IPC(8): G06K9/62
CPCG06F18/214Y02D30/70
Inventor 张剑钟绍宸孙学文王奎
Owner 北京超星未来科技有限公司
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