METHOD OF TRAINING MODEL AND METHOD OF DETERMINING ASSET VALUATION
A method of training a model, a method of determining an asset valuation, a device, a storage medium, and a program product, which relate to a field of artificial intelligence, in particular to fields of deep learning and natural language understanding. A specific implementation can include: determi...
Gespeichert in:
| Hauptverfasser: | , , , , , , |
|---|---|
| Format: | Patent |
| Sprache: | eng |
| Schlagworte: | |
| 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 | Liu, Ji Zhang, Weijia Zhu, Hengshu Xiong, Hui Yu, Sunjie Liu, Hao Dou, Dejing |
| description | A method of training a model, a method of determining an asset valuation, a device, a storage medium, and a program product, which relate to a field of artificial intelligence, in particular to fields of deep learning and natural language understanding. A specific implementation can include: determining an event-level representation according to a first set of feature data; performing a multi-task learning for a first model according to the event-level representation, to obtain first price distribution data, and transmitting the first price distribution data to a central server; determining a first intra-region representation according to a second set of feature data; adding a noise signal to the first intra-region representation, and transmitting the noised intra-region representation to a client; and adjusting a parameter of the first model according to a noised parameter gradient in response to the noised parameter gradient being received from the central server. |
| format | Patent |
| fullrecord | <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_US2023127699A1</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>US2023127699A1</sourcerecordid><originalsourceid>FETCH-epo_espacenet_US2023127699A13</originalsourceid><addsrcrecordid>eNrjZHDydQ3x8HdR8HdTCAly9PTz9HNX8PV3cfVRcPRzUUBIuriGuAb5QuQdg4NdQxTCHH1CHUM8_f14GFjTEnOKU3mhNDeDsptriLOHbmpBfnxqcUFicmpeakl8aLCRgZGxoZG5maWlo6ExcaoAj6csBA</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>METHOD OF TRAINING MODEL AND METHOD OF DETERMINING ASSET VALUATION</title><source>esp@cenet</source><creator>Liu, Ji ; Zhang, Weijia ; Zhu, Hengshu ; Xiong, Hui ; Yu, Sunjie ; Liu, Hao ; Dou, Dejing</creator><creatorcontrib>Liu, Ji ; Zhang, Weijia ; Zhu, Hengshu ; Xiong, Hui ; Yu, Sunjie ; Liu, Hao ; Dou, Dejing</creatorcontrib><description>A method of training a model, a method of determining an asset valuation, a device, a storage medium, and a program product, which relate to a field of artificial intelligence, in particular to fields of deep learning and natural language understanding. A specific implementation can include: determining an event-level representation according to a first set of feature data; performing a multi-task learning for a first model according to the event-level representation, to obtain first price distribution data, and transmitting the first price distribution data to a central server; determining a first intra-region representation according to a second set of feature data; adding a noise signal to the first intra-region representation, and transmitting the noised intra-region representation to a client; and adjusting a parameter of the first model according to a noised parameter gradient in response to the noised parameter gradient being received from the central server.</description><language>eng</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; COUNTING ; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES ; PHYSICS ; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR</subject><creationdate>2023</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=20230427&DB=EPODOC&CC=US&NR=2023127699A1$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25563,76318</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20230427&DB=EPODOC&CC=US&NR=2023127699A1$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>Liu, Ji</creatorcontrib><creatorcontrib>Zhang, Weijia</creatorcontrib><creatorcontrib>Zhu, Hengshu</creatorcontrib><creatorcontrib>Xiong, Hui</creatorcontrib><creatorcontrib>Yu, Sunjie</creatorcontrib><creatorcontrib>Liu, Hao</creatorcontrib><creatorcontrib>Dou, Dejing</creatorcontrib><title>METHOD OF TRAINING MODEL AND METHOD OF DETERMINING ASSET VALUATION</title><description>A method of training a model, a method of determining an asset valuation, a device, a storage medium, and a program product, which relate to a field of artificial intelligence, in particular to fields of deep learning and natural language understanding. A specific implementation can include: determining an event-level representation according to a first set of feature data; performing a multi-task learning for a first model according to the event-level representation, to obtain first price distribution data, and transmitting the first price distribution data to a central server; determining a first intra-region representation according to a second set of feature data; adding a noise signal to the first intra-region representation, and transmitting the noised intra-region representation to a client; and adjusting a parameter of the first model according to a noised parameter gradient in response to the noised parameter gradient being received from the central server.</description><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES</subject><subject>PHYSICS</subject><subject>SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2023</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZHDydQ3x8HdR8HdTCAly9PTz9HNX8PV3cfVRcPRzUUBIuriGuAb5QuQdg4NdQxTCHH1CHUM8_f14GFjTEnOKU3mhNDeDsptriLOHbmpBfnxqcUFicmpeakl8aLCRgZGxoZG5maWlo6ExcaoAj6csBA</recordid><startdate>20230427</startdate><enddate>20230427</enddate><creator>Liu, Ji</creator><creator>Zhang, Weijia</creator><creator>Zhu, Hengshu</creator><creator>Xiong, Hui</creator><creator>Yu, Sunjie</creator><creator>Liu, Hao</creator><creator>Dou, Dejing</creator><scope>EVB</scope></search><sort><creationdate>20230427</creationdate><title>METHOD OF TRAINING MODEL AND METHOD OF DETERMINING ASSET VALUATION</title><author>Liu, Ji ; Zhang, Weijia ; Zhu, Hengshu ; Xiong, Hui ; Yu, Sunjie ; Liu, Hao ; Dou, Dejing</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_US2023127699A13</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng</language><creationdate>2023</creationdate><topic>CALCULATING</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES</topic><topic>PHYSICS</topic><topic>SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR</topic><toplevel>online_resources</toplevel><creatorcontrib>Liu, Ji</creatorcontrib><creatorcontrib>Zhang, Weijia</creatorcontrib><creatorcontrib>Zhu, Hengshu</creatorcontrib><creatorcontrib>Xiong, Hui</creatorcontrib><creatorcontrib>Yu, Sunjie</creatorcontrib><creatorcontrib>Liu, Hao</creatorcontrib><creatorcontrib>Dou, Dejing</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Liu, Ji</au><au>Zhang, Weijia</au><au>Zhu, Hengshu</au><au>Xiong, Hui</au><au>Yu, Sunjie</au><au>Liu, Hao</au><au>Dou, Dejing</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>METHOD OF TRAINING MODEL AND METHOD OF DETERMINING ASSET VALUATION</title><date>2023-04-27</date><risdate>2023</risdate><abstract>A method of training a model, a method of determining an asset valuation, a device, a storage medium, and a program product, which relate to a field of artificial intelligence, in particular to fields of deep learning and natural language understanding. A specific implementation can include: determining an event-level representation according to a first set of feature data; performing a multi-task learning for a first model according to the event-level representation, to obtain first price distribution data, and transmitting the first price distribution data to a central server; determining a first intra-region representation according to a second set of feature data; adding a noise signal to the first intra-region representation, and transmitting the noised intra-region representation to a client; and adjusting a parameter of the first model according to a noised parameter gradient in response to the noised parameter gradient being received from the central server.</abstract><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | |
| ispartof | |
| issn | |
| language | eng |
| recordid | cdi_epo_espacenet_US2023127699A1 |
| source | esp@cenet |
| subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES PHYSICS SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR |
| title | METHOD OF TRAINING MODEL AND METHOD OF DETERMINING ASSET VALUATION |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-10T10%3A51%3A28IST&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=Liu,%20Ji&rft.date=2023-04-27&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3EUS2023127699A1%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 |