Invention Grant
- Patent Title: Skimming data sequences using recurrent neural networks
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Application No.: US16865747Application Date: 2020-05-04
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Publication No.: US11048875B2Publication Date: 2021-06-29
- Inventor: Quoc V. Le , Hongrae Lee , Wei Yu
- 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: G06F40/30
- IPC: G06F40/30 ; G06F40/284 ; G06N3/04 ; G06N3/08 ; G06F40/289

Abstract:
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for processing sequential data. In one aspect, a computer-implemented method includes receiving a request to generate a system output for an input data sequence, the input data sequence including a plurality of tokens. One or more tokens may be designated as tokens to be skipped. When a token has not been designated as a token to be skipped, the token is processed using a recurrent neural network to update a current internal state of the recurrent neural network. The system output is generated from the final internal state of the recurrent neural network.
Public/Granted literature
- US20200265191A1 SKIMMING DATA SEQUENCES USING RECURRENT NEURAL NETWORKS Public/Granted day:2020-08-20
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