Invention Application
- Patent Title: MULTI-TASK RECURRENT NEURAL NETWORKS
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Application No.: US16262785Application Date: 2019-01-30
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Publication No.: US20200160150A1Publication Date: 2020-05-21
- Inventor: Milad Olia Hashemi , Jamie Alexander Smith , Kevin Jordan Swersky
- Applicant: Google LLC
- Main IPC: G06N3/04
- IPC: G06N3/04 ; G06N3/08 ; G06F3/06

Abstract:
Methods, systems, and apparatus, including computer programs encoded on computer storage media, relating to multi-task recurrent neural networks. One of the methods includes maintaining data specifying, for a recurrent neural network, a separate internal state for each of a plurality of memory regions; receiving a current input; identifying a particular memory region of the memory access address defined by the current input; selecting, from the internal states specified in the maintained data, the internal state for the particular memory region; processing, in accordance with the selected internal state for the particular memory region, the current input in the sequence of inputs using the recurrent neural network to: generate an output, the output defining a probability distribution of a predicted memory access address, and update the selected internal state of the particular memory region; and associating the updated selected internal state with the particular memory region in the maintained data.
Public/Granted literature
- US11416733B2 Multi-task recurrent neural networks Public/Granted day:2022-08-16
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