公开(公告)号：US20230066545A1

公开(公告)日：2023-03-02

申请号：US17964563

申请日：2022-10-12

Applicant: Google LLC

Inventor： Hugh Brendan McMahan ,  Kunal Talwar ,  Li Zhang ,  Daniel Ramage

IPC: G06N20/00 ,  G06K9/62 ,  G06F8/65 ,  H04L67/10 ,  G06F21/62 ,  H04L9/40

Abstract: Systems and methods for learning differentially private machine-learned models are provided. A computing system can include one or more server computing devices comprising one or more processors and one or more non-transitory computer-readable media that collectively store instructions that, when executed by the one or more processors cause the one or more server computing devices to perform operations. The operations can include selecting a subset of client computing devices from a pool of available client computing devices; providing a machine-learned model to the selected client computing devices; receiving, from each selected client computing device, a local update for the machine-learned model; determining a differentially private aggregate of the local updates; and determining an updated machine-learned model based at least in part on the data-weighted average of the local updates.

公开(公告)号：US11475350B2

公开(公告)日：2022-10-18

申请号：US15877196

申请日：2018-01-22

Applicant: Google LLC

Inventor： Hugh Brendan McMahan ,  Kunal Talwar ,  Li Zhang ,  Daniel Ramage

IPC: G06F9/44 ,  G06N20/00 ,  G06K9/62 ,  G06F8/65 ,  H04L67/10 ,  G06F21/62 ,  H04L9/40

Abstract: Systems and methods for learning differentially private machine-learned models are provided. A computing system can include one or more server computing devices comprising one or more processors and one or more non-transitory computer-readable media that collectively store instructions that, when executed by the one or more processors cause the one or more server computing devices to perform operations. The operations can include selecting a subset of client computing devices from a pool of available client computing devices; providing a machine-learned model to the selected client computing devices; receiving, from each selected client computing device, a local update for the machine-learned model; determining a differentially private aggregate of the local updates; and determining an updated machine-learned model based at least in part on the data-weighted average of the local updates.

公开(公告)号：US10397472B2

公开(公告)日：2019-08-27

申请号：US15901450

申请日：2018-02-21

Applicant: Google LLC

Inventor： Alexandros Andre Chaaraoui ,  Carlos Hernandez Esteban ,  Li Zhang ,  Steven Maxwell Seitz

IPC: H04N5/232 ,  G03B27/00 ,  G06F3/01

Abstract: Aspects of the disclosure relate to capturing panoramic images using a computing device. For example, the computing device may record a set of video frames and tracking features each including one or more features that appear in two or more video frames of the set of video frames within the set of video frames may be determined. A set of frame-based features based on the displacement of the tracking features between two or more video frames of the set of video frames may be determined by the computing device. A set of historical feature values based on the set of frame-based features may also be determined by the computing device. The computing device may determine then whether a user is attempting to capture a panoramic image based on the set of historical feature values. In response, the computing device may capture a panoramic image.