VALIDATING PERFORMANCE OF A NEURAL NETWORK TRAINED USING LABELED TRAINING DATA
A method for validating performance of a neural network trained using labeled training and validation data is provided. The method includes: determining proposed model parameters as potential updates to the neural network using the labeled validation data, performing a short-term validation on the p...
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description | A method for validating performance of a neural network trained using labeled training and validation data is provided. The method includes: determining proposed model parameters as potential updates to the neural network using the labeled validation data, performing a short-term validation on the proposed model parameters applied to the neural network based on the labeled validation data by comparing a first performance output based on the proposed model parameters and a second performance output based on currently-existing model parameters applied to the neural network, updating the currently-existing model parameters with the proposed model parameters when the second performance output outperforms the first performance output with respect to the labeled validation data, performing a long-term validation on the updated currently-existing model parameters applied to the neural network, and performing an operation when a difference between the original model parameters and the updated currently-existing model parameters lies within a threshold. |
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The method includes: determining proposed model parameters as potential updates to the neural network using the labeled validation data, performing a short-term validation on the proposed model parameters applied to the neural network based on the labeled validation data by comparing a first performance output based on the proposed model parameters and a second performance output based on currently-existing model parameters applied to the neural network, updating the currently-existing model parameters with the proposed model parameters when the second performance output outperforms the first performance output with respect to the labeled validation data, performing a long-term validation on the updated currently-existing model parameters applied to the neural network, and performing an operation when a difference between the original model parameters and the updated currently-existing model parameters lies within a threshold.</description><language>eng</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; COUNTING ; ELECTRIC DIGITAL DATA PROCESSING ; PHYSICS</subject><creationdate>2021</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20210225&DB=EPODOC&CC=US&NR=2021056411A1$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,776,881,25542,76290</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20210225&DB=EPODOC&CC=US&NR=2021056411A1$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>JUNG, Namsoon</creatorcontrib><title>VALIDATING PERFORMANCE OF A NEURAL NETWORK TRAINED USING LABELED TRAINING DATA</title><description>A method for validating performance of a neural network trained using labeled training and validation data is provided. 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subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING PHYSICS |
title | VALIDATING PERFORMANCE OF A NEURAL NETWORK TRAINED USING LABELED TRAINING DATA |
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