METHOD FOR DISTRIBUTED TRAINING MODEL, RELEVANT APPARATUS, AND COMPUTER READABLE STORAGE MEDIUM

    公开(公告)号:US20210357814A1

    公开(公告)日:2021-11-18

    申请号:US17362674

    申请日:2021-06-29

    Abstract: The present disclosure provides a method and apparatus for distributed training a model, an electronic device, and a computer readable storage medium. The method may include: performing, for each batch of training samples acquired by a distributed first trainer, model training through a distributed second trainer to obtain gradient information; updating a target parameter in a distributed built-in parameter server according to the gradient information; and performing, in response to determining that training for a preset number of training samples is completed, a parameter exchange between the distributed built-in parameter server and a distributed parameter server through the distributed first trainer to perform a parameter update on the initial model until training for the initial model is completed.

    METHOD AND APPARATUS FOR RECOMMENDING SAMPLE DATA

    公开(公告)号:US20190087685A1

    公开(公告)日:2019-03-21

    申请号:US16102837

    申请日:2018-08-14

    Abstract: The present disclosure proposes a method and an apparatus for recommending sample data. The method may include: inputting a plurality of pieces of sample data to be classified into at least one preset classification model, and acquiring a classifying probability of classifying each piece of sample data into each classification model; acquiring a first distance between each piece of sample data and a classifying boundary of each classification model according to the classifying probability of classifying the piece of sample data into the classification model, in which the classifying boundary of the classification model is configured to distinguish positive and negative sample data; computing a target distance for each piece of sample data according to the first distance between each piece of sample data and the classifying boundary of each classification model.

    SYSTEM AND METHOD FOR AUTOMATIC SECURE DELIVERY OF MODEL

    公开(公告)号:US20210004696A1

    公开(公告)日:2021-01-07

    申请号:US16895350

    申请日:2020-06-08

    Abstract: The present disclosure provides a system and a method for automatic secure delivery of a model, and belongs to the field of delivery technologies of artificial intelligence models. The system includes: a model warehouse, including at least one machine learning model; a prediction warehouse, including at least one prediction module matching metadata of the machine learning model in the model warehouse; and a processing engine, configured to have a function of assembling the machine learning model in the model warehouse and the prediction module in the prediction warehouse; in which the prediction module is configured to have an authentication function and an anti-debugging function, and the processing engine is configured to assemble the machine learning model in the model warehouse and the prediction module in the prediction warehouse which have a metadata matching relationship, and to generate a prediction service after the assembly is completed.

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