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公开(公告)号：US11113289B2
公开(公告)日：2021-09-07
申请号：US15648374
申请日：2017-07-12
Applicant: Apple Inc.
Inventor： Hon Yuk Chan , John M. Hörnkvist , Lun Cui , Vipul Ved Prakash , Anubhav Malhotra , Stanley N. Hung , Julien Freudiger
IPC: G06F16/2457 , G06F16/248 , G06F16/335 , G06F16/9535 , G06N3/08 , G06N20/00 , G06F16/951 , G06N3/04 , G06N20/20
Abstract: A method and apparatus of a device that generates a re-ranking model used to re-rank a plurality of search results on a client device is described. In an exemplary embodiment, the device receives a crowd-sourced intra-domain model from a server, where the intra-domain model is a search result re-ranking model generated based on at least device interactions of a plurality of users interacting with a plurality of other devices. The device further generates a re-ranking model from the crowd-sourced intra-domain model and a local model, where the local model includes private data representing a device user's interaction with that device and the re-ranking model is used to re-rank a plurality of search results.
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公开(公告)号：US20190068628A1
公开(公告)日：2019-02-28
申请号：US16159481
申请日：2018-10-12
Applicant: Apple Inc.
Inventor： Abhradeep Guha Thakurta , Andrew H. Vyrros , Umesh S. Vaishampayan , Gaurav Kapoor , Julien Freudiger , Vipul Ved Prakash , Arnaud Legendre , Steven Duplinsky
CPC classification number: H04L63/1425 , G06F17/2235 , G06F17/2735 , G06F17/276 , G06F21/6254 , G06N20/00 , H04L63/0421
Abstract: Systems and methods are disclosed for generating term frequencies of known terms based on crowdsourced differentially private sketches of the known terms. An asset catalog can be updated with new frequency counts for known terms based on the crowdsourced differentially private sketches. Known terms can have a classification. A client device can maintain a privacy budget for each classification of known terms. Classifications can include emojis, deep links, locations, finance terms, and health terms, etc. A privacy budget ensures that a client does not transmit too much information to a term frequency server, thereby compromising the privacy of the client device.
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公开(公告)号：US12182319B2
公开(公告)日：2024-12-31
申请号：US17190995
申请日：2021-03-03
Applicant: Apple Inc.
Inventor： Deepak Iyer , Jessica Aranda , Cindy M. Barrett , Patrick Coffman , Julien Freudiger , Alexander S. Haas , Nahir A. Khan , Behkish J. Manzari , Kevin M. Miller , Brian Pietsch , Stephen J. Rhee , Stefan Stuerke , Eric L. Wilson
IPC: G06F21/83 , G06F3/04817 , G06F3/04842 , G06F21/12 , G06F21/32
Abstract: Embodiments described herein provide a software-based privacy indicator for a camera and microphone that focuses not purely on hardware status (e.g., on or off), but on whether potentially private data is flowing to the system or an application. If based purely on hardware status, the indicator for an electronic device may be shown in scenarios where no data actually flows to the system or applications. The privacy indicator will be enabled if any camera or microphone data is relayed to the operating system or an application that is executed via the operating system. When the device uses the microphone and camera to capture environmental metadata about the surroundings of the device without providing any audio samples, images, or video frames to the system or an application, the privacy indicator will not be enabled.
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公开(公告)号：US20210166157A1
公开(公告)日：2021-06-03
申请号：US16501132
申请日：2020-01-17
Applicant: Apple Inc.
Inventor： Abhishek Bhowmick , John Duchi , Julien Freudiger , Gaurav Kapoor , Ryan M. Rogers
Abstract: Embodiments described herein provide for a non-transitory machine-readable medium storing instructions to cause one or more processors to perform operations comprising receiving a machine learning model from a server at a client device, training the machine learning model using local data at the client device, generating an update for the machine learning model, the update including a weight vector that represents a difference between the received machine learning model and the trained machine learning model, privatizing the update for the machine learning model, and transmitting the privatized update for the machine learning model to the server.
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公开(公告)号：US11003672B2
公开(公告)日：2021-05-11
申请号：US15648364
申请日：2017-07-12
Applicant: Apple Inc.
Inventor： Hon Yuk Chan , John M. Hörnkvist , Lun Cui , Vipul Ved Prakash , Anubhav Malhotra , Stanley N. Hung , Julien Freudiger
IPC: G06F16/2457 , G06N20/00 , G06F16/248 , G06F16/951 , G06F16/335 , G06F16/9535 , G06N3/04 , G06N20/20 , G06N3/08
Abstract: A method and apparatus of a device that re-rank a plurality of search results is described. In an exemplary embodiment, the device receives a search query from a user and generates the plurality of search results over a plurality of search domains, wherein the plurality of search results is ranked according to a first ranking. The device additionally generates a re-ranking model, where the re-ranking model includes a plurality of intra-domain models that are generated based on at least based on-device interactions of a plurality of users interacting with a plurality of other devices and each of the plurality of search domains corresponds to one of the plurality of intra-domain models. The device further re-ranks the plurality of search results using the re-ranking model and presents the plurality of search results using the second ranking.
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Patent Agency Ranking
公开(公告)号：US09645998B1
公开(公告)日：2017-05-09
申请号：US15275357
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
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.
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公开(公告)号：US11989634B2
公开(公告)日：2024-05-21
申请号：US16501132
申请日：2020-01-17
Applicant: Apple Inc.
Inventor： Abhishek Bhowmick , John Duchi , Julien Freudiger , Gaurav Kapoor , Ryan M. Rogers
Abstract: Embodiments described herein provide for a non-transitory machine-readable medium storing instructions to cause one or more processors to perform operations comprising receiving a machine learning model from a server at a client device, training the machine learning model using local data at the client device, generating an update for the machine learning model, the update including a weight vector that represents a difference between the received machine learning model and the trained machine learning model, privatizing the update for the machine learning model, and transmitting the privatized update for the machine learning model to the server.
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公开(公告)号：US11895105B2
公开(公告)日：2024-02-06
申请号：US17162955
申请日：2021-01-29
Applicant: Apple Inc.
Inventor： James R. Montgomerie , Jessica Aranda , Patrick Coffman , Julien Freudiger , Matthew Hansen Gamble , Ron Huang , Anant Jain , Glen S. Low , Andrey Pokrovskiy , Stephen J. Rhee , Matthew E. Shepherd , Ansh Shukla , Katherine Skinner , Kyle Martin Sluder , Christopher Soli , Christopher K. Thomas , Guy L. Tribble , John Wilander
CPC classification number: H04L63/0807 , H04L63/083 , H04L63/0853 , H04W12/06
Abstract: An access control system is provided to prevent the surreptitious granting of access to privacy related functionality on an electronic device. Software-based events to grant access to device functionality can be validated by confirming that the software event corresponds with a hardware input event. This validation prevents the spoofing of a user interface input that may be used to fraudulently grant access to specific functionality.
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公开(公告)号：US20190097978A1
公开(公告)日：2019-03-28
申请号：US16159473
申请日：2018-10-12
Applicant: Apple Inc.
Inventor： Abhradeep Guha Thakurta , Andrew H. Vyrros , Umesh S. Vaishampayan , Gaurav Kapoor , Julien Freudiger , Vivek Rangarajan Sridhar , Doug Davidson
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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公开(公告)号：US20210400037A1
公开(公告)日：2021-12-23
申请号：US17162955
申请日：2021-01-29
Applicant: Apple Inc.
Inventor： James R. Montgomerie , Jessica Aranda , Patrick Coffman , Julien Freudiger , Matthew Hansen Gamble , Ron Huang , Anant Jain , Glen S. Low , Andrey Pokrovskiy , Stephen J. Rhee , Matthew E. Shepherd , Ansh Shukla , Katherine Skinner , Kyle Martin Sluder , Christopher Soli , Christopher K. Thomas , Guy L. Tribble , John Wilander
Abstract: An access control system is provided to prevent the surreptitious granting of access to privacy related functionality on an electronic device. Software-based events to grant access to device functionality can be validated by confirming that the software event corresponds with a hardware input event. This validation prevents the spoofing of a user interface input that may be used to fraudulently grant access to specific functionality.
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