Invention Grant
- Patent Title: Implicit bridging of machine learning tasks
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Application No.: US16402787Application Date: 2019-05-03
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Publication No.: US10679148B2Publication Date: 2020-06-09
- Inventor: Zhifeng Chen , Michael Schuster , Melvin Jose Johnson Premkumar , Yonghui Wu , Quoc V. Le , Maxim Krikun , Thorsten Brants
- Applicant: Google LLC
- Applicant Address: US CA Mountain View
- Assignee: Google LLC
- Current Assignee: Google LLC
- Current Assignee Address: US CA Mountain View
- Agency: Fish & Richardson P.C.
- Main IPC: G06N20/00
- IPC: G06N20/00 ; G06N3/04 ; G06N3/063 ; G06F40/44 ; G06F40/47

Abstract:
Methods, systems, and apparatus, including computer programs encoded on computer storage media for performing machine learning tasks. One method includes receiving (i) a model input, and (ii) data identifying a first machine learning task to be performed on the model input to generate a first type of model output for the model input; augmenting the model input with an identifier for the first machine learning task to generate an augmented model input; and processing the augmented model input using a machine learning model. An exemplary system applying implicit bridging for machine learning tasks, as described in this specification, trains a machine learning model to perform certain types of machine learning tasks without requiring explicit training data for the certain types of machine learning tasks to be used during training.
Public/Granted literature
- US20190258961A1 IMPLICIT BRIDGING OF MACHINE LEARNING TASKS Public/Granted day:2019-08-22
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