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    PRIVACY PRESERVING MACHINE LEARNING EXPANSION MODELS
    2.
    发明公开
    PRIVACY PRESERVING MACHINE LEARNING EXPANSION MODELS 审中-公开

    公开(公告)号：US20230177543A1

    公开(公告)日：2023-06-08

    申请号：US17543465

    申请日：2021-12-06

    Applicant: Google LLC

    Inventor： Wei Huang ,  Zhenyu Liu ,  Geoffrey Charles Levine ,  Deepa Paranjpe ,  Yipei Wang ,  Robert Istvan Busa-Fekete

    IPC: G06Q30/02 ,  G06Q30/06 ,  G06N20/00

    CPC classification number: G06Q30/0205 ,  G06Q30/0631 ,  G06N20/00

    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for using machine learning models to expand user groups while preserving user privacy and data security are described. In one aspect, a method includes receiving, for a web-based resource, a set of user group identifiers for a set of user interest groups that each include, as members, one or more users that requested content from the web-based resource over a given time period. A seed user list that includes user identifiers for at least a portion of the users in the set of user interest groups is created. A similar audience machine learning model is generated based on a set of one or more feature values corresponding to one or more features of the users corresponding to the user identifiers in the seed user list. A set of similar users is identified using the model.

    SYSTEMS AND METHODS FOR PRESERVING DEVICE PRIVACY
    3.
    发明申请
    SYSTEMS AND METHODS FOR PRESERVING DEVICE PRIVACY 有权

    公开(公告)号：US20220253557A1

    公开(公告)日：2022-08-11

    申请号：US17627033

    申请日：2020-04-16

    Applicant: Google LLC

    Inventor： Michael Kleber ,  Zhenyu Liu ,  Josh Karlin ,  Deepak Ravichandran ,  Nitish John Korula ,  Yijian Bai ,  Jason Hsueh ,  Gang Wang

    IPC: G06F21/62 ,  G06N20/00 ,  H04L67/53 ,  H04L67/50

    Abstract: The present disclosure provides systems and methods for client-side anonymized content selections. The method includes collecting a plurality of identifications of content selection lists, each content selection list associated with the first device and at least one other device. The method includes selecting a first subset of the content selection lists, responsive to a total number of unique device associated with a plurality of content selection lists of the first subset exceeding a threshold. The method includes transmitting a request for an item of content, the request comprising identifications of the content selection lists of the selected first subset. The method includes receiving a first item of content selected by the content server based on the content selection lists of the selected first subset.

    Privacy preserving remarketing
    5.
    发明授权
    Privacy preserving remarketing 有权

    公开(公告)号：US11074369B2

    公开(公告)日：2021-07-27

    申请号：US16524792

    申请日：2019-07-29

    Applicant: GOOGLE LLC

    Inventor： Michael Kleber ,  Zhenyu Liu ,  Josh Karlin ,  Gang Wang ,  Nitish John Korula ,  Yijian Bai ,  Jason Hsueh ,  Deepak Ravichandran

    IPC: G06F21/62 ,  G06N20/00 ,  H04L29/08

    Abstract: The present disclosure provides systems and methods for client-side anonymized content selections. The method includes collecting a plurality of identifications of content selection lists, each content selection list associated with the first device and at least one other device. The method includes selecting a first subset of the content selection lists, responsive to a total number of unique device associated with a plurality of content selection lists of the first subset exceeding a threshold. The method includes transmitting a request for an item of content, the request comprising identifications of the content selection lists of the selected first subset. The method includes receiving a first item of content selected by the content server based on the content selection lists of the selected first subset.

    Local mobile memo for non-interrupting link noting
    6.
    发明授权
    Local mobile memo for non-interrupting link noting 有权

    公开(公告)号：US10129386B1

    公开(公告)日：2018-11-13

    申请号：US15162399

    申请日：2016-05-23

    Applicant: Google LLC

    Inventor： Yifang Liu ,  Zhenyu Liu

    IPC: G06F17/22 ,  H04M1/725 ,  G06F3/0482 ,  G06F3/0488 ,  G06F17/27

    Abstract: Systems, methods, routines and/or techniques for a local mobile memo for non-interrupting link noting are described. One or more embodiments may include a method that may include displaying to a user a page containing a link, receiving a first user input that indicates the link should be saved for potential later processing and saving the link to a local repository so that the link can be processed later. The saving may occur while the page continues to be displayed. The saving may occur without processing the link to perform the associated action. The method may include displaying a list (e.g., including the link) of one or more links saved in the repository, for example, in response to an event that indicates that the user may be interested in viewing links in the link repository.

    ENHANCED MACHINE LEARNING TECHNIQUES USING DIFFERENTIAL PRIVACY AND SELECTIVE DATA AGGREGATION
    7.
    发明申请
    ENHANCED MACHINE LEARNING TECHNIQUES USING DIFFERENTIAL PRIVACY AND SELECTIVE DATA AGGREGATION 有权

    公开(公告)号：US20250111272A1

    公开(公告)日：2025-04-03

    申请号：US18574668

    申请日：2023-04-25

    Applicant: Google LLC

    Inventor： Wei Huang ,  Zhenyu Liu ,  Liang Wang ,  Kumar Rishabh

    IPC: G06N20/00

    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for distributing digital contents to client devices are described. The system obtains, for each user in a set of users, user attribute data and, for a subset of the users, consent data for controlling usage of the user attribute data. The system partitions, based at least on the consent data for the subset of users, the set of users into a first group of users and a second group of users. The system generates a respective training dataset based on the data for each group of user, and uses the datasets to train a machine learning model configured to predict information about one or more users. In particular, the system applies differential privacy to the second training dataset without applying differential privacy to the first training dataset during training.

    DIGITAL COMPONENT PROVISION BASED ON CONTEXTUAL FEATURE DRIVEN AUDIENCE INTEREST PROFILES
    8.
    发明申请
    DIGITAL COMPONENT PROVISION BASED ON CONTEXTUAL FEATURE DRIVEN AUDIENCE INTEREST PROFILES 有权

    公开(公告)号：US20250094508A1

    公开(公告)日：2025-03-20

    申请号：US18577448

    申请日：2023-01-18

    Applicant: Google LLC

    Inventor： Wei Huang ,  Zhenyu Liu ,  Liang Wang ,  Kumar Rishabh

    IPC: G06F16/9535 ,  G06F16/9537

    Abstract: Methods, systems, and media comprising; obtaining, from a client device and during a browsing session conducted by a user, contextual features relating to context within the browsing session, wherein the contextual features do not include any personally-identifiable data; generating, using a trained contextual model and based on the contextual features, an audience interest profile, wherein the audience interest profile represents a prediction of affinity to one or more content categories, wherein the trained contextual model is trained using a set of historical contextual data aggregated from a plurality of prior browsing sessions and audience interest profiles that each represent an affinity to one or more content categories, and wherein the set of historical contextual data does not include any personally-identifiable data; identifying, based on the generated audience interest profile, a digital component for provision; and providing, for display on the client device and during the browsing session, the digital component.

    PRIVACY-PRESERVING DATA PROCESSING FOR CONTENT DISTRIBUTION
    9.
    发明申请
    PRIVACY-PRESERVING DATA PROCESSING FOR CONTENT DISTRIBUTION 有权

    公开(公告)号：US20250086300A1

    公开(公告)日：2025-03-13

    申请号：US18574715

    申请日：2023-04-24

    Applicant: Google LLC

    Inventor： Wei Huang ,  Zhenyu Liu

    IPC: G06F21/62

    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for distributing digital contents to client devices are described. For each of a plurality of client devices, the system receives a digital component request, identifies one or more user attributes of a user based on the digital component request, and sends the identified user attributes to the client device. The system obtains, from a shared storage of each client device, accumulated user attribute data and generates an aggregated user attribute report for a set of aggregation keys using the obtained accumulated user attribute data. The system distributes digital components to the client devices based on distribution parameters adjusted based on the aggregated user attribute report.

    Local Mobile Memo For Non-interrupting Link Noting
    10.
    发明申请
    Local Mobile Memo For Non-interrupting Link Noting 审中-公开

    公开(公告)号：US20190028583A1

    公开(公告)日：2019-01-24

    申请号：US16144608

    申请日：2018-09-27

    Applicant: Google LLC

    Inventor： Yifang Liu ,  Zhenyu Liu

    IPC: H04M1/725 ,  G06F17/27 ,  G06F3/0488 ,  G06F17/22 ,  G06F3/0482

    Abstract: Systems, methods, routines and/or techniques for a local mobile memo for non-interrupting link noting are described. One or more embodiments may include a method that may include displaying to a user a page containing a link, receiving a first user input that indicates the link should be saved for potential later processing and saving the link to a local repository so that the link can be processed later. The saving may occur while the page continues to be displayed. The saving may occur without processing the link to perform the associated action. The method may include displaying a list (e.g., including the link) of one or more links saved in the repository, for example, in response to an event that indicates that the user may be interested in viewing links in the link repository.

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