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Model optimization method, device and equipment and readable storage medium

An optimization method and model technology, applied in the field of deep learning, can solve problems such as weak optimization of deep learning network models and inability to effectively reduce the complexity of deep learning network models, and achieve a balance between accuracy and complexity, reduce complexity, and improve optimization degree of effect

Pending Publication Date: 2022-03-11
CHINA MOBILE COMM LTD RES INST +1
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Problems solved by technology

[0003] Embodiments of the present invention provide a model optimization method, device, device, and readable storage medium to solve the problem that the optimization degree of the existing deep learning network model is weak and the complexity of the deep learning network model cannot be effectively reduced

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  • Model optimization method, device and equipment and readable storage medium
  • Model optimization method, device and equipment and readable storage medium
  • Model optimization method, device and equipment and readable storage medium

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Embodiment Construction

[0027] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0028] In order to obtain the optimal accuracy on a specific data set, when designing the network structure, convolution and pooling layers are continuously added to build a deeper network structure. However, as the network deepens, the increase in accuracy will weaken and gradually reach saturation, and the accuracy may even decrease due to problems such as overfitting. In this process, the complexity of the network will also increase, the amount of c...

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Abstract

The invention provides a model optimization method, device and equipment and a readable storage medium, and relates to the technical field of deep learning, and the model optimization method comprises the steps: determining M network models; determining description lengths of the M network models based on a to-be-analyzed data set; and determining a target network model with the minimum description length from the M network models as an optimized network model, and carrying out data processing based on the optimized network model. In this way, the problems that the optimization degree of an existing deep learning network model is weak, and the complexity of the deep learning network model cannot be effectively reduced are solved.

Description

technical field [0001] The present invention relates to the technical field of deep learning, in particular to a model optimization method, device, equipment and readable storage medium. Background technique [0002] With the rapid development of network technology, deep learning network models are more and more widely used, and deep learning network models are becoming more and more complex. In the application of an overly complex network model, more training data, computing resources, and storage resources are required, and the problem of overfitting is prone to occur. At present, network pruning based on transfer learning is mostly used for model optimization. Network pruning is to compress the width of the network to achieve the purpose of model optimization. In this way, the width of the network is optimized first, and the depth The degree of optimization of the learning network model is weak and cannot effectively reduce the complexity of the deep learning network mod...

Claims

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Application Information

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IPC IPC(8): G06N3/04G06N3/08
CPCG06N3/08G06N3/045
Inventor 马文婷张志鹏徐青青
Owner CHINA MOBILE COMM LTD RES INST
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