View source for 20240012680. TECHNIQUES FOR INTER-CLOUD FEDERATED LEARNING simplified abstract (VMware, Inc.)

=TECHNIQUES FOR INTER-CLOUD FEDERATED LEARNING=


==Organization Name==

[[:Category:VMware, Inc.|VMware, Inc.]]


[[Category:VMware, Inc.]]

==Inventor(s)==

[[:Category:Fangchi Wang of Beijing (CN)|Fangchi Wang of Beijing (CN)]][[Category:Fangchi Wang of Beijing (CN)]]

[[:Category:Hai Ning Zhang of Beijing (CN)|Hai Ning Zhang of Beijing (CN)]][[Category:Hai Ning Zhang of Beijing (CN)]]

[[:Category:Layne Lin Peng of Shanghai (CN)|Layne Lin Peng of Shanghai (CN)]][[Category:Layne Lin Peng of Shanghai (CN)]]

[[:Category:Renming Zhao of Beijing (CN)|Renming Zhao of Beijing (CN)]][[Category:Renming Zhao of Beijing (CN)]]

[[:Category:Siyu Qiu of Beijing (CN)|Siyu Qiu of Beijing (CN)]][[Category:Siyu Qiu of Beijing (CN)]]

==TECHNIQUES FOR INTER-CLOUD FEDERATED LEARNING - A simplified explanation of the abstract==


This abstract first appeared for US patent application 20240012680 titled 'TECHNIQUES FOR INTER-CLOUD FEDERATED LEARNING

==Simplified Explanation==

The abstract of the patent application describes techniques for facilitating inter-cloud federated learning (FL). 

* An FL lifecycle manager is provided to centrally manage the lifecycles of FL components across different cloud platforms. 
* The FL lifecycle manager enables operations such as deploying/installing, updating, and uninstalling FL components on the cloud platforms. 
* An FL job manager is also provided to centrally manage the execution of FL training runs (FL jobs) on the deployed FL components. 
* The FL job manager allows users to define job parameters and configuration, initiate and monitor job status, take actions on running jobs, and collect job results.

Potential applications of this technology:

* Federated learning in multi-cloud environments.
* Collaborative machine learning across different cloud platforms.
* Centralized management of FL lifecycles and job execution.

Problems solved by this technology:

* Simplifies the management of FL components across different cloud platforms.
* Provides a centralized approach for deploying, updating, and uninstalling FL components.
* Streamlines the execution and monitoring of FL training runs.

Benefits of this technology:

* Improved efficiency in managing FL components and job execution.
* Enhanced collaboration and coordination in multi-cloud federated learning.
* Simplified deployment and maintenance of FL components across cloud platforms.


==Original Abstract Submitted==

techniques for facilitating inter-cloud federated learning (fl) are provided. in one set of embodiments, these techniques comprise an fl lifecycle manager that enables users to centrally manage the lifecycles of fl components across different cloud platforms. the lifecycle management operations enabled by the fl lifecycle manager can include deploying/installing fl components on the cloud platforms, updating the components, and uninstalling the components. in a further set of embodiments, these techniques comprise an fl job manager that enables users to centrally manage the execution of fl training runs (i.e., fl jobs) on fl components that have been deployed via the fl lifecycle manager. for example, the fl job manager can enable users to define the parameters and configuration of an fl job, initiate the job, monitor the job's status, take actions on the running job, and collect the job's results.



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