Machine learning method, device and system of distributed system, equipment and storage medium

A distributed system and machine learning technology, applied in the field of computer-readable storage media and machine learning, can solve problems such as the inability to guarantee the security of private data, achieve the effects of protecting private data, saving equipment resources, and improving security

Active Publication Date: 2021-02-09
TENCENT TECH (SHENZHEN) CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, during the use of the distributed machine learning technology provided by related technologies, due to the existence of a third party, the security of private data between internal devices cannot be guaranteed

Method used

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  • Machine learning method, device and system of distributed system, equipment and storage medium
  • Machine learning method, device and system of distributed system, equipment and storage medium
  • Machine learning method, device and system of distributed system, equipment and storage medium

Examples

Experimental program
Comparison scheme
Effect test

example 1

[0198] Example 1. The machine learning device of the distributed system is a mobile terminal application program and module

[0199] The machine learning device of the distributed system in the embodiment of the present application can be provided as a software module designed using programming languages ​​such as software C / C++, Java, etc., embedded in various mobile applications based on systems such as Android or iOS (with executable The instructions are stored in the storage medium of the mobile terminal and executed by the processor of the mobile terminal), so as to directly use the computing resources of the mobile terminal itself to complete relevant information recommendation tasks, and regularly or irregularly transmit the processing results to Remote server, or save locally on the mobile terminal.

example 2

[0200] Example 2. Machine learning devices for distributed systems are server applications and platforms

[0201] The machine learning device 555 of the distributed system in the embodiment of the present application can be provided as application software designed using C / C++, Java and other programming languages ​​or as a dedicated software module in a large-scale software system, running on the server side (in the form of executable instructions) stored in the server-side storage medium and run by the server-side processor), and the server uses its own computing resources to complete relevant information recommendation tasks.

[0202] The embodiment of the present application can also be provided as a distributed and parallel computing platform composed of multiple servers, equipped with a customized and easy-to-interact network (Web) interface or other user interfaces (UI, User Interface), forming a user interface for individuals, Information recommendation platforms...

example 3

[0203] Example 3. The machine learning device of the distributed system is a server-side application program interface (API, Application Program Interface) and plug-ins

[0204] The machine learning device 555 of the distributed system in the embodiment of the present application can be provided as a server-side API or plug-in for users to call to execute the machine learning method of the distributed system of the embodiment of the present application, and embedded in various applications middle.

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PUM

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Abstract

The invention provides a machine learning method, device and system of a distributed system, electronic equipment and a computer readable storage medium. An artificial intelligence technology is involved. The method comprises the following steps that: master equipment performs homomorphic encryption on a global gradient scalar of a machine learning model, and sends the obtained encrypted global gradient scalar to slave equipment; the slave equipment determines an encrypted local gradient corresponding to the slave equipment based on the encrypted global gradient scalar, feature data stored bythe slave equipment for the training sample and a local model parameter corresponding to the slave equipment; the master equipment and the slave equipment jointly decrypt the encrypted local gradientcorresponding to the slave equipment to obtain a decryption local gradient corresponding to the slave equipment; and the slave equipment updates a local model parameter corresponding to the slave equipment based on the decrypted local gradient corresponding to the slave equipment. According to the invention, the safety of the training data can be ensured.

Description

technical field [0001] The present application relates to artificial intelligence technology, and in particular to a distributed system machine learning method, device, system, electronic equipment, and computer-readable storage medium. Background technique [0002] Artificial Intelligence (AI) is a comprehensive technology of computer science. By studying the design principles and implementation methods of various intelligent machines, it enables machines to have the functions of perception, reasoning and decision-making. Artificial intelligence technology is a comprehensive subject that involves a wide range of fields, such as natural language processing technology and machine learning / deep learning. With the development of technology, artificial intelligence technology will be applied in more fields and play an increasingly important role. increasingly important value. [0003] The larger the scale of the machine learning model, the training on a single machine has gradu...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F21/60G06N20/20
CPCG06F21/602G06N20/20
Inventor 刘洋
Owner TENCENT TECH (SHENZHEN) CO LTD
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