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Method and system for carrying out model training based on selectable private data

A technology for model training and privacy data, applied in computing models, digital data protection, electrical digital data processing, etc.

Active Publication Date: 2020-04-28
ALIPAY (HANGZHOU) INFORMATION TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, in the process of multi-party data cooperation, issues such as data security and model security are involved

Method used

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  • Method and system for carrying out model training based on selectable private data
  • Method and system for carrying out model training based on selectable private data
  • Method and system for carrying out model training based on selectable private data

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Embodiment Construction

[0014] In order to more clearly describe the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings that need to be used in the description of the embodiments. Obviously, the drawings in the following description are just some examples or embodiments of the application. For those of ordinary skill in the art, without creative work, the application can be applied to the application according to these drawings. Other similar scenarios. Unless it is obvious from the language environment or otherwise stated, the same reference numerals in the figures represent the same structure or operation.

[0015] It should be understood that the “system”, “device”, “unit” and / or “module” used in this specification is a method for distinguishing different components, elements, parts, parts, or assemblies of different levels. However, if other words can achieve the same purpose, the words can be replaced by other expressions.

[0016] A...

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Abstract

One or more embodiments of the present specification relate to a method and a system for model training based on selectable private data. The method comprises the following steps that: a label holdingterminal receives an operation product of first type data and second type data at least from a first terminal; wherein the first type of data and the second type of data correspond to different privacy levels; the label holding terminal determines a data accumulation value based on the operation product of the received first type of data and second type of data and the second data of the label holding terminal; the label holding terminal determines a loss value at least based on a model jointly trained by the label holding terminal and the first terminal based on the data accumulation value and the sample label; the loss value participates in calculation of a gradient value; wherein the gradient value is used for updating the joint training model; wherein the first terminal holds first data, and the first data comprises a first type of data and a second type of data; the label holding terminal holds second data and a sample label; the first data and the second data correspond to the same training sample.

Description

Technical field [0001] One or more embodiments of this specification relate to multi-party data cooperation, and in particular to a method and system for model training based on optional private data. Background technique [0002] In data analysis, data mining, economic forecasting and other fields, machine learning models can be used to analyze and discover potential data value. Since the data held by a single data owner may be incomplete, it is difficult to accurately describe the target. In order to obtain better model prediction results, the joint training of the model is carried out through the data cooperation of multiple data owners Has been widely used. But in the process of multi-party data cooperation, issues such as data security and model security are involved. [0003] Therefore, it is necessary to propose a safe joint modeling scheme based on multi-party data. Summary of the invention [0004] An aspect of the embodiments of this specification provides a method for ...

Claims

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Application Information

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IPC IPC(8): G06N20/00G06F21/62
CPCG06N20/00G06F21/6245
Inventor 陈超超王力周俊
Owner ALIPAY (HANGZHOU) INFORMATION TECH CO LTD