Federal learning method, storage medium, terminal, server and federal learning system
A learning method and storage medium technology, applied in integrated learning and other directions, can solve problems such as inability to effectively take into account terminal power consumption and overall training time, inability to analyze data on mobile terminals, and violation of data analysis, so as to reduce overall training time and reduce training. time, and the effect of improving training efficiency
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
Method used
Image
Examples
Example Embodiment
[0065]Example one
[0066]Such asfigure 1 As shown, the federal learning system of the present invention includes a server 10 and a plurality of terminals 20, and the server 10 can communicate with the terminal 20. The basic workflow of the federal learning system is that each terminal 20 transmits the respective training information to the server 10, the server 10 acquires the constraint time according to the training information of the respective terminal 20, and the terminal 20 acquires the training parameters according to the constraint time. Training parameters complete model training. The constraint time is used to cause the terminal to complete the model training within the constraint time, the training parameters to consume minimal energy consumption when the terminal is completed. This federal learning system reduces overall training time and reduces energy consumption.
[0067]The federal learning system of the present embodiment is described in detail below from the server 10 a...
Example Embodiment
[0068]Example 2
[0069]Such asfigure 2 As shown, the federal learning method of the second embodiment includes the following steps:
[0070]Step S10: The server 10 receives the training information sent from the terminal.
[0071]Before you start training, the server 10 needs to collect training information of each terminal 20 in advance. The training information includes hardware information and preset training data amount, wherein the hardware information includes information such as processor information of the terminal, mainly refers to information such as CPU frequency, CPU cycle, and preset training data refers to each terminal. Contains the number of training data, for example, for image recognition tasks, the number of training data refers to how many pictures in the terminal contain.
[0072]Step S20: The server 10 acquires the constraint time according to the training information, which is used to complete the model training within the constraint time.
[0073]Specifically, this step S2...
Example Embodiment
[0096]Example three
[0097]The third embodiment discloses a computer readable storage medium that stores a federal learning program that implements the federal learning method as described in Example 2 when the federal learning program is executed.
PUM
Abstract
Description
Claims
Application Information
- R&D Engineer
- R&D Manager
- IP Professional
- Industry Leading Data Capabilities
- Powerful AI technology
- Patent DNA Extraction
Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.
© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap