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US Patent 11954597 Using embedding functions with a deep network

Patent 11954597 was granted and assigned to Google on April, 2024 by the United States Patent and Trademark Office.

OverviewStructured DataIssuesContributors
Is a
Patent
Patent
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Current Assignee
Google
Google
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Date Filed
October 24, 2022
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Date of Patent
April 9, 2024
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Patent Applicant
Google
Google
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Patent Application Number
17972466
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Patent Citations
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US Patent 7689006 Biometric convolution using multiple biometrics
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US Patent 7428524 Large scale data storage in sparse tables
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US Patent 7548928 Data compression of large scale data stored in sparse tables
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US Patent 7567973 Storing a sparse table using locality groups
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US Patent 7624074 Methods for feature selection in a learning machine
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US Patent 7661128 Secure login credentials for substantially anonymous users
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US Patent 8234228 Method for training a learning machine having a deep multi-layered network with labeled and unlabeled training data
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US Patent 8484351 Associating application-specific methods with tables used for data storage
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US Patent 8489529 Deep convex network with joint use of nonlinear random projection, Restricted Boltzmann Machine and batch-based parallelizable optimization
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US Patent 8768870 Training a model using parameter server shards
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•••
Patent Inventor Names
David W. Sculley, II
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Kai Chen
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Julian P. Grady
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Jeffrey A. Dean
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Gregory S. Corrado
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Gary R. Holt
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Sharat Chikkerur
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Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
11954597
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Patent Primary Examiner
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Kamran Afshar
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CPC Code
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G06F 2207/483
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G06F 15/00
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G06F 7/483
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G06F 15/76
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G06K 9/6255
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G06K 9/6268
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G06F 17/16
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G06N 99/00
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G06N 5/025
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G06N 3/084
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•••

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