MACHINE LEARNING WITH INSTANCE-DEPENDENT LABEL NOISE

    公开(公告)号:US20230259762A1

    公开(公告)日:2023-08-17

    申请号:US17972302

    申请日:2022-10-24

    CPC classification number: G06N3/08

    Abstract: An artificial intelligence (AI) classifier is trained using supervised training and an effect of noise in the training data is reduced. The training data includes observed noisy labels. A posterior transition matrix (PTM) is used to minimize, in a statistical sense, a cross entropy between a noisy label and a function of the classifier output. A loss function using the PTM is provided to use in training the classifier. The classifier provides final output predictions with good performance even with the existence of noisy labels. Also, information fusion is included in the classifier training using the PTM and an estimated noise transition matrix (NTM) to reduce estimation error at the classifier output.

    METHOD AND APPARATUS FOR ANALYZING APPLICATION PROGRAM BY ANALYSIS OF SOURCE CODE
    2.
    发明申请
    METHOD AND APPARATUS FOR ANALYZING APPLICATION PROGRAM BY ANALYSIS OF SOURCE CODE 审中-公开
    通过分析源代码分析应用程序的方法和装置

    公开(公告)号:US20130227524A1

    公开(公告)日:2013-08-29

    申请号:US13776170

    申请日:2013-02-25

    CPC classification number: G06F8/71 G06F8/75

    Abstract: A method and an apparatus for analyzing source codes of an application program having open source codes and analyzing features which are used in the application program are provided. The method includes analyzing the application program according to the source codes in the application program, determining application program configuration information used in the application program, and classifying and outputting the application program configuration information according to the determined application program configuration information.

    Abstract translation: 提供一种用于分析具有开放源代码和分析在应用程序中使用的特征的应用程序的源代码的方法和装置。 该方法包括根据应用程序中的源代码分析应用程序,确定应用程序中使用的应用程序配置信息,并根据所确定的应用程序配置信息对应用程序配置信息进行分类和输出。

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