Title:
TRAINING METHOD, APPARATUS AND SYSTEM FOR INTEGRATED LEARNING MODEL, AND RELATED DEVICE
Document Type and Number:
WIPO Patent Application WO/2022/161081
Kind Code:
A1
Abstract:
A training method for an integrated learning model, which method is applied to a model training system comprising a control node and a working node. The method comprises: when training an integrated learning model, a control node acquiring a training request for the integrated learning model; generating, according to the training request, a training task set comprising a plurality of training tasks; and then, the control node respectively sending the training tasks in the training task set to a plurality of working nodes in a working node set, wherein each training task is executed by one working node, each training task is used for training at least one learning sub-model in the integrated learning model, and different training tasks are used for training different learning sub-models. A training result of each learning sub-model can be processed by a working node, such that the amount of data needing to be communicated between working nodes during the process of training the learning sub-models can be effectively reduced, and the training efficiency and success rate of an integrated learning model are improved.
Inventors:
YU SI (CN)
JIA JIAFENG (CN)
XIONG QIN (CN)
WANG GONGYI (CN)
JIA JIAFENG (CN)
XIONG QIN (CN)
WANG GONGYI (CN)
Application Number:
PCT/CN2021/142240
Publication Date:
August 04, 2022
Filing Date:
December 28, 2021
Export Citation:
Assignee:
HUAWEI TECH CO LTD (CN)
International Classes:
G06N20/20
Foreign References:
| CN111444019A | 2020-07-24 | |||
| CN109409738A | 2019-03-01 | |||
| CN111860835A | 2020-10-30 | |||
| CN106815644A | 2017-06-09 | |||
| CN111768006A | 2020-10-13 | |||
| US20180374105A1 | 2018-12-27 |
Other References:
SONG CHUANGCHUANG, FANG YONG; HUANG CHENG; LIU LIANG: "Password strength estimation model based on ensemble learning", JOURNAL OF COMPUTER APPLICATIONS, JISUANJI YINGYONG, CN, vol. 38, no. 5, 10 May 2018 (2018-05-10), CN , pages 1383 - 1388, XP055954980, ISSN: 1001-9081, DOI: 10.11772/j.issn.1001-9081.2017102516
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