MACHINE LEARNING FOR DETECTING AND MODIFYING FAULTY CONTROLS

In some aspects, a computing system may use machine learning to determine whether a control is faulty or generate recommendations to make a modification to a control. may identify a portion of problematic computer code that implements the faulty control through the use of machine learning. A computi...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Hauptverfasser:	EDWARDS, Joshua, HERGENROEDER, Albert, MAIMAN, Tyler, CUNNINGHAM, Sarah Jane, KWOK, Jennifer
Format:	Patent
Sprache:	eng
Schlagworte:	CONTROL OR REGULATING SYSTEMS IN GENERAL CONTROLLING FUNCTIONAL ELEMENTS OF SUCH SYSTEMS MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS ORELEMENTS PHYSICS REGULATING
Online-Zugang:	Volltext bestellen
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

container_end_page
container_issue
container_start_page
container_title
container_volume
creator	EDWARDS, Joshua HERGENROEDER, Albert MAIMAN, Tyler CUNNINGHAM, Sarah Jane KWOK, Jennifer
description	In some aspects, a computing system may use machine learning to determine whether a control is faulty or generate recommendations to make a modification to a control. may identify a portion of problematic computer code that implements the faulty control through the use of machine learning. A computing system may use machine learning to generate embeddings that map incident data and control data (e.g., computer-readable code of a control) to the same vector space. Further, a computing system may use a weighting mechanism that may be used to weight each sample used to train a machine learning model, which may allow a model to train more efficiently.
format	Patent
fullrecord	<record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_US2024168472A1</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>US2024168472A1</sourcerecordid><originalsourceid>FETCH-epo_espacenet_US2024168472A13</originalsourceid><addsrcrecordid>eNrjZLDxdXT28PRzVfBxdQzy8_RzV3DzD1JwcQ1xdQ4B8Rz9XBR8_V083SLBco6hPiGRCs7-fiFB_j7BPAysaYk5xam8UJqbQdnNNcTZQze1ID8-tbggMTk1L7UkPjTYyMDIxNDMwsTcyNHQmDhVAKLPKoQ</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>MACHINE LEARNING FOR DETECTING AND MODIFYING FAULTY CONTROLS</title><source>esp@cenet</source><creator>EDWARDS, Joshua ; HERGENROEDER, Albert ; MAIMAN, Tyler ; CUNNINGHAM, Sarah Jane ; KWOK, Jennifer</creator><creatorcontrib>EDWARDS, Joshua ; HERGENROEDER, Albert ; MAIMAN, Tyler ; CUNNINGHAM, Sarah Jane ; KWOK, Jennifer</creatorcontrib><description>In some aspects, a computing system may use machine learning to determine whether a control is faulty or generate recommendations to make a modification to a control. may identify a portion of problematic computer code that implements the faulty control through the use of machine learning. A computing system may use machine learning to generate embeddings that map incident data and control data (e.g., computer-readable code of a control) to the same vector space. Further, a computing system may use a weighting mechanism that may be used to weight each sample used to train a machine learning model, which may allow a model to train more efficiently.</description><language>eng</language><subject>CONTROL OR REGULATING SYSTEMS IN GENERAL ; CONTROLLING ; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS ; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS ORELEMENTS ; PHYSICS ; REGULATING</subject><creationdate>2024</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=20240523&DB=EPODOC&CC=US&NR=2024168472A1$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,776,881,25542,76289</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20240523&DB=EPODOC&CC=US&NR=2024168472A1$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>EDWARDS, Joshua</creatorcontrib><creatorcontrib>HERGENROEDER, Albert</creatorcontrib><creatorcontrib>MAIMAN, Tyler</creatorcontrib><creatorcontrib>CUNNINGHAM, Sarah Jane</creatorcontrib><creatorcontrib>KWOK, Jennifer</creatorcontrib><title>MACHINE LEARNING FOR DETECTING AND MODIFYING FAULTY CONTROLS</title><description>In some aspects, a computing system may use machine learning to determine whether a control is faulty or generate recommendations to make a modification to a control. may identify a portion of problematic computer code that implements the faulty control through the use of machine learning. A computing system may use machine learning to generate embeddings that map incident data and control data (e.g., computer-readable code of a control) to the same vector space. Further, a computing system may use a weighting mechanism that may be used to weight each sample used to train a machine learning model, which may allow a model to train more efficiently.</description><subject>CONTROL OR REGULATING SYSTEMS IN GENERAL</subject><subject>CONTROLLING</subject><subject>FUNCTIONAL ELEMENTS OF SUCH SYSTEMS</subject><subject>MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS ORELEMENTS</subject><subject>PHYSICS</subject><subject>REGULATING</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2024</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZLDxdXT28PRzVfBxdQzy8_RzV3DzD1JwcQ1xdQ4B8Rz9XBR8_V083SLBco6hPiGRCs7-fiFB_j7BPAysaYk5xam8UJqbQdnNNcTZQze1ID8-tbggMTk1L7UkPjTYyMDIxNDMwsTcyNHQmDhVAKLPKoQ</recordid><startdate>20240523</startdate><enddate>20240523</enddate><creator>EDWARDS, Joshua</creator><creator>HERGENROEDER, Albert</creator><creator>MAIMAN, Tyler</creator><creator>CUNNINGHAM, Sarah Jane</creator><creator>KWOK, Jennifer</creator><scope>EVB</scope></search><sort><creationdate>20240523</creationdate><title>MACHINE LEARNING FOR DETECTING AND MODIFYING FAULTY CONTROLS</title><author>EDWARDS, Joshua ; HERGENROEDER, Albert ; MAIMAN, Tyler ; CUNNINGHAM, Sarah Jane ; KWOK, Jennifer</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_US2024168472A13</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng</language><creationdate>2024</creationdate><topic>CONTROL OR REGULATING SYSTEMS IN GENERAL</topic><topic>CONTROLLING</topic><topic>FUNCTIONAL ELEMENTS OF SUCH SYSTEMS</topic><topic>MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS ORELEMENTS</topic><topic>PHYSICS</topic><topic>REGULATING</topic><toplevel>online_resources</toplevel><creatorcontrib>EDWARDS, Joshua</creatorcontrib><creatorcontrib>HERGENROEDER, Albert</creatorcontrib><creatorcontrib>MAIMAN, Tyler</creatorcontrib><creatorcontrib>CUNNINGHAM, Sarah Jane</creatorcontrib><creatorcontrib>KWOK, Jennifer</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>EDWARDS, Joshua</au><au>HERGENROEDER, Albert</au><au>MAIMAN, Tyler</au><au>CUNNINGHAM, Sarah Jane</au><au>KWOK, Jennifer</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>MACHINE LEARNING FOR DETECTING AND MODIFYING FAULTY CONTROLS</title><date>2024-05-23</date><risdate>2024</risdate><abstract>In some aspects, a computing system may use machine learning to determine whether a control is faulty or generate recommendations to make a modification to a control. may identify a portion of problematic computer code that implements the faulty control through the use of machine learning. A computing system may use machine learning to generate embeddings that map incident data and control data (e.g., computer-readable code of a control) to the same vector space. Further, a computing system may use a weighting mechanism that may be used to weight each sample used to train a machine learning model, which may allow a model to train more efficiently.</abstract><oa>free_for_read</oa></addata></record>
fulltext	fulltext_linktorsrc
identifier
ispartof
issn
language	eng
recordid	cdi_epo_espacenet_US2024168472A1
source	esp@cenet
subjects	CONTROL OR REGULATING SYSTEMS IN GENERAL CONTROLLING FUNCTIONAL ELEMENTS OF SUCH SYSTEMS MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS ORELEMENTS PHYSICS REGULATING
title	MACHINE LEARNING FOR DETECTING AND MODIFYING FAULTY CONTROLS
url	https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-05T14%3A34%3A11IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-epo_EVB&rft_val_fmt=info:ofi/fmt:kev:mtx:patent&rft.genre=patent&rft.au=EDWARDS,%20Joshua&rft.date=2024-05-23&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3EUS2024168472A1%3C/epo_EVB%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true