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Model parameter training method, server, system and storage medium

A training method and server technology, applied in the fields of systems and storage media, servers, and model parameter training methods, can solve problems such as long time-consuming prediction model parameter training, and achieve improved resource utilization, reduced transmission, and reduced iterative training time Effect

Pending Publication Date: 2021-08-20
BEIJING DAJIA INTERNET INFORMATION TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0004] The present disclosure provides a model parameter training method, server, system and storage medium to at least solve the problem in the related art that the parameter training of the prediction model takes a long time

Method used

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  • Model parameter training method, server, system and storage medium
  • Model parameter training method, server, system and storage medium
  • Model parameter training method, server, system and storage medium

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Embodiment Construction

[0037] In order to enable ordinary persons in the art to better understand the technical solutions of the present disclosure, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the accompanying drawings.

[0038]It should be noted that the terms "first" and "second" in the specification and claims of the present disclosure and the above drawings are used to distinguish similar objects, but not necessarily used to describe a specific sequence or sequence. It is to be understood that the data so used are interchangeable under appropriate circumstances such that the embodiments of the disclosure described herein can be practiced in sequences other than those illustrated or described herein. The implementations described in the following exemplary examples do not represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatuses and methods consis...

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Abstract

The invention relates to a model parameter training method, a server, a system and a storage medium, and relates to the technical field of machine learning. The embodiment of the invention at least solves the problem of long time consumption of parameter training of a prediction model in related technologies. The method is applied to a working server of a distributed system, and comprises the following steps: acquiring a current embedding parameter corresponding to a training sample of a current batch; obtaining network parameters currently stored in the working server from the working server; based on the training sample of the current batch, performing iterative training on the current embedded parameter and a network parameter currently stored by the working server to obtain an embedded parameter gradient and a network parameter gradient; updating the current embedded parameter based on the embedded parameter gradient, and synchronizing the updated embedded parameter to a parameter server; and updating the network parameters currently stored by the working server based on the network parameter gradient.

Description

technical field [0001] The present disclosure relates to the technical field of machine learning, and in particular to a model parameter training method, server, system and storage medium. Background technique [0002] At present, related technologies use deep neural networks as a predictive model for determining click-through-rate (CTR), and the network parameters in the predictive model are large-scale Sparse model training obtained. Specifically, the PS framework includes a parameter server and a working server. During training, the working server is used to obtain model parameters from the parameter server after obtaining training samples from the outside, and perform iterative training on the model parameters, and use the trained The gradient of the model parameters is sent to the parameter server, and the parameter server updates the stored model parameters according to the gradient of the model parameters. [0003] However, since the parameter server mainly uses the...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/08G06N3/04
CPCG06N3/08G06N3/045
Inventor 董星
Owner BEIJING DAJIA INTERNET INFORMATION TECH CO LTD