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US Patent 11423259 Trained model approximation

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Is a
Patent
Patent
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Patent attributes

Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
114232590
Date of Patent
August 23, 2022
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Patent Application Number
158388130
Date Filed
December 12, 2017
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Patent Citations
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US Patent 10685262 Object recognition based on boosting binary convolutional neural network features
Patent Citations Received
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US Patent 11657334 Techniques for deriving and/or leveraging application-centric model metric
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US Patent 11699108 Techniques for deriving and/or leveraging application-centric model metric
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Patent Primary Examiner
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Evren Seven
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A system that can create an approximated model from a trained machine learning model (such as a neural network) where the approximated model can operate using fewer computing resources than the original trained model. The system can create the approximated model without the voluminous training data used to create the original trained model. The system can rely on just the data describing the trained model and an indicator as to how closely the approximated model should correspond to the original model and/or the desired savings of computing resources. Various lossless and/or lossy approximations may be performed to obtain multiple approximated models that may be substituted for the trained model during runtime operations to achieve significant speed/cost savings over operation of the original trained model.

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