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    EMBEDDING OPTIMIZATION FOR A MACHINE LEARNING MODEL
    121.
    发明公开
    EMBEDDING OPTIMIZATION FOR A MACHINE LEARNING MODEL 审中-公开

    公开(公告)号：US20230229736A1

    公开(公告)日：2023-07-20

    申请号：US17579566

    申请日：2022-01-19

    Applicant: Lemon Inc.

    Inventor： Xia XIAO ,  Ming CHEN ,  Youlong CHENG

    IPC: G06K9/62 ,  G06F17/16 ,  G06N20/00

    CPC classification number: G06K9/6257 ,  G06F17/16 ,  G06N20/00

    Abstract: Embodiments of the present disclosure relate to feature selection via an ensemble of gating layers. According to embodiments of the present disclosure, a set of model parameter values for a machine learning model and a set of embedding vectors are determined for an input field of the machine learning model. The machine learning model is constructed to map an input sample in the input field to an embedding vector in the embedding vectors and process the embedding vector with the model parameter values to generate a model output. The machine learning model is trained by updating the model parameter values and the embedding vectors according to at least a first training objective function, the first training objective function being based on an orthogonality metric between embedding vectors in the embedding vectors and based on a difference between the model output and a ground-truth model output.

    Accessing user accounts and data from any computing device
    122.
    发明授权
    Accessing user accounts and data from any computing device 有权

    公开(公告)号：US11693986B1

    公开(公告)日：2023-07-04

    申请号：US17877662

    申请日：2022-07-29

    Applicant: Lemon Inc. ,  Beijing Youzhuju Network Technology Co., Ltd.

    Inventor： Viacheslav Dubeyko ,  Jian Wang

    IPC: G06F21/62 ,  H04L9/40 ,  G06F21/60 ,  H04L29/06

    CPC classification number: G06F21/6218 ,  G06F21/604 ,  H04L63/0838 ,  H04L63/0861 ,  H04L63/105

    Abstract: The present disclosure describes techniques for accessing user accounts and data from any computing device. It may be determined whether an account of a user exists in a cloud service in response to receiving information associated with the user from any computing device. Data associated with the account may be stored by the cloud service. There may be a plurality of types of data associated with a plurality of security levels. The plurality of security levels may correspond to different security requirements. The data associated with the account may belong to at least one of the plurality of types of data. An instance of the account may be deployed to the computing device in response to determining that the account exists in the cloud service. The instance of the account may enable the user to access services via the computing device.

    OFFLOADING COMPUTATION BASED ON EXTENDED INSTRUCTION SET ARCHITECTURE
    123.
    发明公开
    OFFLOADING COMPUTATION BASED ON EXTENDED INSTRUCTION SET ARCHITECTURE 审中-公开

    公开(公告)号：US20230205532A1

    公开(公告)日：2023-06-29

    申请号：US18118367

    申请日：2023-03-07

    Applicant: Lemon Inc. ,  Beijing Youzhuju Network Technology Co., Ltd.

    Inventor： Viacheslav Dubeyko ,  Jian Wang

    IPC: G06F9/30

    CPC classification number: G06F9/30189 ,  G06F9/30145

    Abstract: The present disclosure describes techniques for offloading computation based on an extended instruction set architecture (ISA). The extended ISA may be created based on identifying functions executed multiple times by a central processing unit (CPU). The extended ISA may comprise hashes corresponding to the functions and identifiers of extended operations associated with the functions. The extended operations may be converted from original operations of the functions. The extended operations may be executable by a storage device. The storage device may be associated with at least one computational core. Code may be synthesized based at least in part on the extended ISA. Computation of the synthesized code may be offloaded into the storage device.

    Operational point sample group in coded video
    124.
    发明授权
    Operational point sample group in coded video 有权

    公开(公告)号：US11683529B2

    公开(公告)日：2023-06-20

    申请号：US17473425

    申请日：2021-09-13

    Applicant: Lemon Inc.

    Inventor： Ye-Kui Wang

    IPC: H04N19/70 ,  H04N19/172 ,  H04N19/30 ,  H04N19/169

    CPC classification number: H04N19/70 ,  H04N19/172 ,  H04N19/188 ,  H04N19/30

    Abstract: Systems, methods and apparatus for visual media data processing are described. One method includes performing a conversion between a visual media data and a visual media file that stores a bitstream of the visual media data in multiple tracks according to a format rule that specifies that the file-level information includes a syntax element that identifies one or more tracks from the multiple tracks that contain a specific type of sample group that includes operation point information.

    FEATURE SELECTION VIA AN ENSEMBLE OF GATING LAYERS
    125.
    发明公开
    FEATURE SELECTION VIA AN ENSEMBLE OF GATING LAYERS 审中-公开

    公开(公告)号：US20230169391A1

    公开(公告)日：2023-06-01

    申请号：US17537185

    申请日：2021-11-29

    Applicant: Lemon Inc.

    Inventor： Ming Chen ,  Xia Xiao ,  Youlong Cheng

    IPC: G06N20/00

    CPC classification number: G06N20/00

    Abstract: Embodiments of the present disclosure relate to feature selection via an ensemble of gating layers. According to embodiments of the present disclosure, a plurality of gating layers is provided to be trained together with a machine learning model. At each update step, one of the plurality of gating layers is selected to perform gating parameter value update together with model parameter value update of the machine learning model. After the iterative update process, a set of target gating parameter values is determined from a plurality of sets of gating parameter values of the plurality of gating layers after the iterative update, and can be used to select a target subset of features to be conveyed from one layer to a next layer in the machine learning model.

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