公开(公告)号：US20220004929A1

公开(公告)日：2022-01-06

申请号：US17479364

申请日：2021-09-20

Applicant: Google Inc.

Inventor： Pannag Sanketi ,  Wolfgang Grieskamp ,  Daniel Ramage ,  Hrishikesh Aradhye ,  Shiyu Hu

IPC: G06N20/00 ,  G06N5/04

Abstract: The present disclosure provides systems and methods for on-device machine learning. In particular, the present disclosure is directed to an on-device machine learning platform and associated techniques that enable on-device prediction, training, example collection, and/or other machine learning tasks or functionality. The on-device machine learning platform can include a context provider that securely injects context features into collected training examples and/or client-provided input data used to generate predictions/inferences. Thus, the on-device machine learning platform can enable centralized training example collection, model training, and usage of machine-learned models as a service to applications or other clients.

公开(公告)号：US11138517B2

公开(公告)日：2021-10-05

申请号：US15674910

申请日：2017-08-11

Applicant: Google Inc.

Inventor： Pannag Sanketi ,  Wolfgang Grieskamp ,  Daniel Ramage ,  Hrishikesh Aradhye ,  Shiyu Hu

IPC: G06N20/00 ,  G06N5/04

Abstract: The present disclosure provides systems and methods for on-device machine learning. In particular, the present disclosure is directed to an on-device machine learning platform and associated techniques that enable on-device prediction, training, example collection, and/or other machine learning tasks or functionality. The on-device machine learning platform can include a context provider that securely injects context features into collected training examples and/or client-provided input data used to generate predictions/inferences. Thus, the on-device machine learning platform can enable centralized training example collection, model training, and usage of machine-learned models as a service to applications or other clients.

公开(公告)号：US20190050749A1

公开(公告)日：2019-02-14

申请号：US15674910

申请日：2017-08-11

Applicant: Google Inc.

Inventor： Pannag Sanketi ,  Wolfgang Grieskamp ,  Daniel Ramage ,  Hrishikesh Aradhye ,  Shiyu Hu

IPC: G06N99/00 ,  G06N5/04

Abstract: The present disclosure provides systems and methods for on-device machine learning. In particular, the present disclosure is directed to an on-device machine learning platform and associated techniques that enable on-device prediction, training, example collection, and/or other machine learning tasks or functionality. The on-device machine learning platform can include a context provider that securely injects context features into collected training examples and/or client-provided input data used to generate predictions/inferences. Thus, the on-device machine learning platform can enable centralized training example collection, model training, and usage of machine-learned models as a service to applications or other clients.