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    • 1. 发明申请
    • Executing Machine-Learning Models
    • US20220327428A1
    • 2022-10-13
    • US17616369
    • 2019-06-04
    • Telefonaktiebolaget LM Ericsson (publ)
    • Bin SunRafia InamAneta Vulgarakis FeljanKonstantinos Vandikas
    • G06N20/20G06K9/62H04L67/10
    • Embodiments described herein provided methods and apparatus for executing a machine-learning model. A first machine-learning model, based on a first set of data and using a machine-learning algorithm, is developed at a first node. A second machine-learning model, based on the first machine-learning model and a second set of data, and using the machine-learning algorithm, is developed at a second node. Information about a difference between the first machine-learning algorithm, at a second node machine-learning model and the second machine-learning model is communicated from the second node to the first node. A request for execution of a machine-learning model is received at the first node. Responsive to receiving the request for the execution of the machine-learning model, information indicative of an execution policy is obtained at the first node. Finally, depending on the obtained information indicative of an execution policy, either, at the first node, a machine-learning model based on the first machine-learning model and the information about a difference between the first machine-learning model and the second machine-learning model is executed to obtain a result; or the first machine-learning model is partially executed at the first node, and the second machine-learning model is partially executed at the second node, to obtain a result.