Joint modeling method and device

A modeling method and federated technology, applied in computer security devices, computing models, character and pattern recognition, etc., can solve problems such as difficulty in establishing a federated learning model and small number of samples

Pending Publication Date: 2021-05-18
CHINA UNIONPAY
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Problems solved by technology

[0005] This application provides a joint modeling method and device to solve the problem that the number of samples is too small in the proces...

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  • Joint modeling method and device
  • Joint modeling method and device
  • Joint modeling method and device

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Embodiment Construction

[0064] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, rather than 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.

[0065] In recent years, financial institutions hope to integrate data resources from all parties to optimize their own application models. However, considering the risk of data privacy leakage, it has been impossible to carry out data cooperation. In order to break the data silos, institutions began to adopt a solution based on federated learning technology when conducting cross-institutional data cooperation. The main implementation is as ...

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Abstract

The embodiment of the invention relates to the field of machine learning, in particular to a joint modeling method and device, which are used for improving model training efficiency and accuracy on the basis of protecting data security in a multi-party computing process. The method comprises the following steps: a first modeling node determines a first output result of first feature data based on a federated learning model, and sends a first encrypted output result obtained by encrypting the first output result to each second modeling node; the first modeling node receives a second encryption evaluation result sent by each second modeling node; the first modeling node determines a total encryption evaluation result of the federated learning model according to the first label data and each second encryption evaluation result, and decrypts the total encryption evaluation result to obtain a total model evaluation result; and the first modeling node decrypts the total encryption evaluation result to obtain a total evaluation result, determines an update gradient value, and updates a first model parameter of the first modeling node in the iteration process based on the update gradient value.

Description

technical field [0001] The invention relates to the field of machine learning, in particular to a joint modeling method and device. Background technique [0002] Federated learning is a machine learning framework that can help different organizations to jointly use and model data while meeting the requirements of user privacy protection, data security and government regulations. Specifically, federated learning needs to solve such a problem: on the premise that the data of each enterprise does not go out of the local area, a virtual shared model can be established through parameter exchange and optimization under the encryption mechanism. The performance of this common model is similar to the model trained by aggregating data from all parties. The data joint modeling scheme does not leak user privacy and complies with the principle of data security protection. [0003] In the existing scheme, only the modeling initiator can provide label data and initiate modeling, and the...

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Application Information

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IPC IPC(8): G06F21/60G06K9/62G06N20/00
CPCG06F21/602G06N20/00G06F18/214
Inventor 罗舟何东杰
Owner CHINA UNIONPAY
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