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    Differential privacy with cloud data
    1.
    发明授权
    Differential privacy with cloud data 有权

    公开(公告)号：US11496286B2

    公开(公告)日：2022-11-08

    申请号：US15815611

    申请日：2017-11-16

    Applicant: Apple Inc.

    Inventor： William T. Duffy ,  Andrew H. Vyrros ,  Yannis Minadakis ,  Andrew R. Byde ,  Giulia Pagallo

    IPC: H04L9/00 ,  G06F21/62 ,  G06F40/20 ,  G06F40/117 ,  H04L9/08

    Abstract: Embodiments described herein enable data associated with a large plurality of users to be analyzed without compromising the privacy of the user data. In one embodiment, a user can opt-in to allow analysis of clear text of the user's emails. An analysis process can then be performed in which an analysis service receives clear text of an email of a client device; processes the clear text of the email into one or more tokens having one or more tags; enriches one or more tokens in the processed email using data associated with a user of the client device and the one or more tags; and processes the clear text and one or more enriched tokens to generate a data set of one or more feature vectors.

    PRIVATIZED MACHINE LEARNING USING GENERATIVE ADVERSARIAL NETWORKS
    2.
    发明申请
    PRIVATIZED MACHINE LEARNING USING GENERATIVE ADVERSARIAL NETWORKS 审中-公开

    公开(公告)号：US20190244138A1

    公开(公告)日：2019-08-08

    申请号：US15892246

    申请日：2018-02-08

    Applicant: Apple Inc.

    Inventor： Abhishek Bhowmick ,  Andrew H. Vyrros ,  Ryan M. Rogers

    IPC: G06N99/00 ,  H04L29/08

    CPC classification number: G06N20/00 ,  H04L9/008 ,  H04L67/10

    Abstract: One embodiment provides for a mobile electronic device comprising a non-transitory machine-readable medium to store instructions, the instructions to cause the mobile electronic device to receive a set of labeled data from a server; receive a unit of data from the server, the unit of data of a same type of data as the set of labeled data; determine a proposed label for the unit of data via a machine learning model on the mobile electronic device, the machine learning model to determine the proposed label for the unit of data based on the set of labeled data from the server and a set of unlabeled data associated with the mobile electronic device; encode the proposed label via a privacy algorithm to generate a privatized encoding of the proposed label; and transmit the privatized encoding of the proposed label to the server.

    Synchronizing handles for user accounts across multiple electronic devices
    4.
    发明授权
    Synchronizing handles for user accounts across multiple electronic devices 有权

    公开(公告)号：US09645966B2

    公开(公告)日：2017-05-09

    申请号：US13675902

    申请日：2012-11-13

    Applicant: Apple Inc.

    Inventor： Justin E. Santamaria ,  Justin M. N. Wood ,  Andrew H. Vyrros

    IPC: G06F15/173 ,  H04L29/06

    CPC classification number: G06F15/173 ,  H04L61/15 ,  H04L63/0823 ,  H04L63/102

    Abstract: The disclosed embodiments provide a system that manages access to a user account from an electronic device. The system includes an identity service that provides a device token for the electronic device and a set of handles associated with the user account to the electronic device. Next, the identity service receives, from the electronic device, a handle registration containing one or more selected handles from the set of handles. Finally, the identity service transmits an identity certificate comprising an association between the selected handles and the electronic device to the electronic device, wherein the identity certificate and the association are used to route data associated with the selected handles to and from the electronic device.

    Learning new words
    5.
    发明授权
    Learning new words 有权
    学习新词

    公开(公告)号：US09594741B1

    公开(公告)日：2017-03-14

    申请号：US15275356

    申请日：2016-09-24

    Applicant: Apple Inc.

    Inventor： Abhradeep Guha Thakurta ,  Andrew H. Vyrros ,  Umesh S. Vaishampayan ,  Gaurav Kapoor ,  Julien Freudiger ,  Vivek Rangarajan Sridhar ,  Doug Davidson

    IPC: G06F17/27 ,  G06N99/00

    CPC classification number: G06F17/2765 ,  G06F17/16 ,  G06F17/2705 ,  G06F17/2735 ,  G06F17/277 ,  G06F17/30737 ,  G06N99/005

    Abstract: Systems and methods are disclosed for a server learning new words generated by user client devices in a crowdsourced manner while maintaining local differential privacy of client devices. A client device can determine that a word typed on the client device is a new word that is not contained in a dictionary or asset catalog on the client device. New words can be grouped in classifications such as entertainment, health, finance, etc. A differential privacy system on the client device can comprise a privacy budget for each classification of new words. If there is privacy budget available for the classification, then one or more new terms in a classification can be sent to new term learning server, and the privacy budget for the classification reduced. The privacy budget can be periodically replenished.

    Abstract translation: 公开了系统和方法，用于服务器以众包方式学习由用户客户端设备生成的新词，同时保持客户端设备的本地差异隐私。 客户端设备可以确定在客户端设备上键入的单词是不包含在客户端设备上的字典或资产目录中的新单词。 新词可以分类为娱乐，健康，财务等分类。客户端设备上的差异隐私系统可以包括每个新词分类的隐私预算。 如果有可用于分类的隐私预算，则可以将分类中的一个或多个新术语发送到新术语学习服务器，并且减少分类的隐私预算。 隐私预算可以定期补充。

    Distributed labeling for supervised learning
    7.
    发明授权
    Distributed labeling for supervised learning 有权

    公开(公告)号：US12260331B2

    公开(公告)日：2025-03-25

    申请号：US18225656

    申请日：2023-07-24

    Applicant: Apple Inc.

    Inventor： Abhishek Bhowmick ,  Ryan M. Rogers ,  Umesh S. Vaishampayan ,  Andrew H. Vyrros

    IPC: G06N3/08 ,  G06N3/04 ,  G06N3/044 ,  G06N3/045 ,  G06N3/10

    Abstract: Embodiments described herein provide a technique to crowdsource labeling of training data for a machine learning model while maintaining the privacy of the data provided by crowdsourcing participants. Client devices can be used to generate proposed labels for a unit of data to be used in a training dataset. One or more privacy mechanisms are used to protect user data when transmitting the data to a server. The server can aggregate the proposed labels and use the most frequently proposed labels for an element as the label for the element when generating training data for the machine learning model. The machine learning model is then trained using the crowdsourced labels to improve the accuracy of the model.

    Learning new words
    10.
    发明授权
    Learning new words 有权

    公开(公告)号：US10133725B2

    公开(公告)日：2018-11-20

    申请号：US15477921

    申请日：2017-04-03

    Applicant: Apple Inc.

    Inventor： Abhradeep Guha Thakurta ,  Andrew H. Vyrros ,  Umesh S. Vaishampayan ,  Gaurav Kapoor ,  Julien Freudiger ,  Vivek Rangarajan Sridhar ,  Doug Davidson

    IPC: G06F17/27 ,  G06N99/00 ,  G06F17/16 ,  G06F17/30

    Abstract: Systems and methods are disclosed for a server learning new words generated by user client devices in a crowdsourced manner while maintaining local differential privacy of client devices. A client device can determine that a word typed on the client device is a new word that is not contained in a dictionary or asset catalog on the client device. New words can be grouped in classifications such as entertainment, health, finance, etc. A differential privacy system on the client device can comprise a privacy budget for each classification of new words. If there is privacy budget available for the classification, then one or more new terms in a classification can be sent to new term learning server, and the privacy budget for the classification reduced. The privacy budget can be periodically replenished.

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