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Model training method and device based on quantum computing

A technology for model training and quantum computing, applied in the field of quantum computing, which can solve problems such as difficulty in completing training tasks

Pending Publication Date: 2021-11-02
北京量子信息科学研究院
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, since the complexity of the optimization training process for the factorization machine model is linearly related to its parameter dimension, its training task becomes more and more difficult to complete with the abundance of user and product information

Method used

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  • Model training method and device based on quantum computing
  • Model training method and device based on quantum computing
  • Model training method and device based on quantum computing

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Embodiment Construction

[0038] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments It is a part of embodiments of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0039] As mentioned earlier, when training some machine learning models such as decomposition machine models, since the complexity of the optimization process (usually the training process) of these models is linearly related to its parameter dimension, the complexity of the training process The degree will increase rapidly as the processing ...

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Abstract

The embodiment of the invention provides a model training method based on quantum computing. The method comprises the steps: acquiring a training data set of a first model and initial parameters of the first model; aiming at the training data set and the initial parameters, setting a quantum circuit according to a Newton method; and running the quantum circuit to obtain optimization parameters of the first model.

Description

technical field [0001] The invention relates to the field of quantum computing, in particular to a model training method and device based on quantum computing. Background technique [0002] Recommender systems are used in many business domains. For example, user product recommendation, including e-commerce product recommendation, short video push, etc., is the core task of almost all resource-integrated network platforms. Using machine learning models in recommendation systems to select recommended products is a commonly used technical means in the industry. Some of these schemes, such as using factorization machine models, work well when the historical interaction information between users and products is sparse. However, since the complexity of the optimization training process for the factorization machine model is linearly related to its parameter dimension, its training task becomes more and more difficult to complete with the abundance of user and product information...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N10/00G06N20/00
CPCG06N10/00G06N20/00
Inventor 龙桂鲁高攀
Owner 北京量子信息科学研究院