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US Patent 11948062 Compressed recurrent neural network models

Patent 11948062 was granted and assigned to Google on April, 2024 by the United States Patent and Trademark Office.

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Contents

Is a
Patent
Patent
1

Patent attributes

Patent Applicant
Google
Google
1
Current Assignee
Google
Google
1
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
1
Patent Number
119480621
Patent Inventor Names
Ouais Alsharif1
Antoine Jean Bruguier1
Ian C. McGraw1
Rohit Prakash Prabhavalkar1
Date of Patent
April 2, 2024
1
Patent Application Number
171129661
Date Filed
December 4, 2020
1
Patent Citations
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US Patent 10229356 Error tolerant neural network model compression
1
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US Patent 10783900 Convolutional, long short-term memory, fully connected deep neural networks
1
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US Patent 10515312 Neural network model compaction using selective unit removal
1
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US Patent 8874496 Encoding and decoding machine with recurrent neural networks
1
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US Patent 10078794 System and method for improved general object detection using neural networks
1
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US Patent 10091140 Context-sensitive generation of conversational responses
1
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US Patent 10217018 System and method for processing images using online tensor robust principal component analysis
1
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US Patent 10223635 Model compression and fine-tuning
1
Patent Primary Examiner
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Miranda M Huang
1
CPC Code
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G05B 2219/40326
1
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G06F 17/16
1
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G06N 3/04
1
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G06N 3/084
1
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G06N 20/00
1
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G06N 3/049
1
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G06N 3/08
1
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G05B 2219/33025
1
Patent abstract

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for implementing a compressed recurrent neural network (RNN). One of the systems includes a compressed RNN, the compressed RNN comprising a plurality of recurrent layers, wherein each of the recurrent layers has a respective recurrent weight matrix and a respective inter-layer weight matrix, and wherein at least one of recurrent layers is compressed such that a respective recurrent weight matrix of the compressed layer is defined by a first compressed weight matrix and a projection matrix and a respective inter-layer weight matrix of the compressed layer is defined by a second compressed weight matrix and the projection matrix.

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