18455574. MODEL TRAINING METHOD AND APPARATUS simplified abstract (HUAWEI TECHNOLOGIES CO., LTD.)

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MODEL TRAINING METHOD AND APPARATUS

Organization Name

HUAWEI TECHNOLOGIES CO., LTD.

Inventor(s)

Yang Xin of Shanghai (CN)

Weiwei Chong of Shenzhen (CN)

Xiaobo Wu of Shenzhen (CN)

Yali Yan of Shanghai (CN)

MODEL TRAINING METHOD AND APPARATUS - A simplified explanation of the abstract

This abstract first appeared for US patent application 18455574 titled 'MODEL TRAINING METHOD AND APPARATUS

Simplified Explanation

The patent application describes an application that improves the efficiency of horizontal federated training in a hybrid mode by allowing clients to flexibly report local model information to either a cloud server or an edge server.

  • The method obtains capability information of the client, including first and second capability information.
  • Based on the capability information, the method determines whether the client should report model information to the cloud server or the edge server.
  • The method sends indication information to the client, instructing it to report the model information to the appropriate server.

Potential Applications

  • This technology can be applied in machine learning and artificial intelligence systems that use horizontal federated training methods.
  • It can be used in scenarios where clients have different capabilities and need to report their local model information to either a cloud server or an edge server.

Problems Solved

  • The technology solves the problem of inefficient horizontal federated training in a hybrid mode.
  • It addresses the challenge of selecting the appropriate server for clients to report their local model information based on their capabilities.

Benefits

  • The method improves the efficiency of horizontal federated training by allowing clients to flexibly report their local model information.
  • It optimizes the training process by selecting the most suitable server for clients to report their information.
  • The technology enhances the overall performance of machine learning and artificial intelligence systems.


Original Abstract Submitted

This application provides a model training method and apparatus. The method includes: obtaining first capability information and second capability information of a client; determining, based on the first capability information and the second capability information, that the client reports model information to a cloud server or an edge server; and sending first indication information to the client. The first indication information indicates the client to report the model information to the cloud server or the edge server. According to the model training method and apparatus provided in this application, in a horizontal federated training method in a hybrid mode, a manner of reporting local model information by the client may be flexibly selected based on capability information of the client, so that horizontal federated training efficiency can be improved.

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