{"id":"https://openalex.org/W3169777530","doi":"https://doi.org/10.1109/tnnls.2021.3084195","title":"Adversarial Caching Training: Unsupervised Inductive Network Representation Learning on Large-Scale Graphs","display_name":"Adversarial Caching Training: Unsupervised Inductive Network Representation Learning on Large-Scale Graphs","publication_year":2021,"publication_date":"2021-06-10","ids":{"openalex":"https://openalex.org/W3169777530","doi":"https://doi.org/10.1109/tnnls.2021.3084195","mag":"3169777530","pmid":"https://pubmed.ncbi.nlm.nih.gov/34111002"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2021.3084195","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2021.3084195","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5045191293","display_name":"Junyang Chen","orcid":"https://orcid.org/0000-0002-1139-8654"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Junyang Chen","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-1139-8654","affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066286956","display_name":"Zhiguo Gong","orcid":"https://orcid.org/0000-0002-4588-890X"},"institutions":[{"id":"https://openalex.org/I204512498","display_name":"University of Macau","ror":"https://ror.org/01r4q9n85","country_code":"MO","type":"education","lineage":["https://openalex.org/I204512498"]},{"id":"https://openalex.org/I6469544","display_name":"City University of Macau","ror":"https://ror.org/04gpd4q15","country_code":"MO","type":"education","lineage":["https://openalex.org/I6469544"]}],"countries":["MO"],"is_corresponding":false,"raw_author_name":"Zhiguo Gong","raw_affiliation_strings":["Department of Computer Information Science, State Key Laboratory of Internet of Things for Smart City, University of Macau, Macau, China"],"raw_orcid":"https://orcid.org/0000-0002-4588-890X","affiliations":[{"raw_affiliation_string":"Department of Computer Information Science, State Key Laboratory of Internet of Things for Smart City, University of Macau, Macau, China","institution_ids":["https://openalex.org/I6469544","https://openalex.org/I204512498"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Wei Wang","orcid":"https://orcid.org/0000-0002-0307-0296"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Wang","raw_affiliation_strings":["School of Intelligent Systems Engineering, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-0307-0296","affiliations":[{"raw_affiliation_string":"School of Intelligent Systems Engineering, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100390494","display_name":"Cong Wang","orcid":"https://orcid.org/0000-0002-6068-0103"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Cong Wang","raw_affiliation_strings":["Department of Computing, The Hong Kong Polytechnic University, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0002-6068-0103","affiliations":[{"raw_affiliation_string":"Department of Computing, The Hong Kong Polytechnic University, Hong Kong","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022889808","display_name":"Zhenghua Xu","orcid":"https://orcid.org/0000-0002-6719-7333"},"institutions":[{"id":"https://openalex.org/I184843921","display_name":"Hebei University of Technology","ror":"https://ror.org/018hded08","country_code":"CN","type":"education","lineage":["https://openalex.org/I184843921"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenghua Xu","raw_affiliation_strings":["State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin, China","institution_ids":["https://openalex.org/I184843921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083333420","display_name":"Jianming Lv","orcid":"https://orcid.org/0000-0003-3691-4755"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianming Lv","raw_affiliation_strings":["School of Computer Science and Engineering, South China University of Technology, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-3691-4755","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100365967","display_name":"Xueliang Li","orcid":"https://orcid.org/0000-0002-8928-9933"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xueliang Li","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-8928-9933","affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001188748","display_name":"Kaishun Wu","orcid":"https://orcid.org/0000-0003-2216-0737"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kaishun Wu","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0003-2216-0737","affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101500385","display_name":"Weiwen Liu","orcid":"https://orcid.org/0000-0002-9148-3997"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Weiwen Liu","raw_affiliation_strings":["Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0002-9148-3997","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5045191293"],"corresponding_institution_ids":["https://openalex.org/I180726961"],"apc_list":null,"apc_paid":null,"fwci":3.4978,"has_fulltext":false,"cited_by_count":39,"citation_normalized_percentile":{"value":0.93731953,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"33","issue":"12","first_page":"7079","last_page":"7090"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9957000017166138,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9835000038146973,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6693063378334045},{"id":"https://openalex.org/keywords/vertex","display_name":"Vertex (graph theory)","score":0.6351945996284485},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6045047044754028},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.48164382576942444},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.45711827278137207},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4536121189594269},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4246969521045685},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.41973134875297546},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4180223345756531},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.41147711873054504},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3922322392463684}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6693063378334045},{"id":"https://openalex.org/C80899671","wikidata":"https://www.wikidata.org/wiki/Q1304193","display_name":"Vertex (graph theory)","level":3,"score":0.6351945996284485},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6045047044754028},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.48164382576942444},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.45711827278137207},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4536121189594269},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4246969521045685},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.41973134875297546},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4180223345756531},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.41147711873054504},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3922322392463684},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2021.3084195","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2021.3084195","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:34111002","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34111002","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1170000390","display_name":null,"funder_award_id":"U2001207","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1270258229","display_name":null,"funder_award_id":"61876065","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6332103343","display_name":null,"funder_award_id":"61902249","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8095065719","display_name":null,"funder_award_id":"2019YFB1600704","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G8812220829","display_name":null,"funder_award_id":"61872248","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1646152356","https://openalex.org/W1888005072","https://openalex.org/W2022322548","https://openalex.org/W2112796928","https://openalex.org/W2118585731","https://openalex.org/W2119717200","https://openalex.org/W2154851992","https://openalex.org/W2155027007","https://openalex.org/W2162630660","https://openalex.org/W2624431344","https://openalex.org/W2768104274","https://openalex.org/W2788284887","https://openalex.org/W2807021761","https://openalex.org/W2903396356","https://openalex.org/W2905224888","https://openalex.org/W2905267911","https://openalex.org/W2911286998","https://openalex.org/W2912636151","https://openalex.org/W2946108624","https://openalex.org/W2949182780","https://openalex.org/W2952726221","https://openalex.org/W2962756421","https://openalex.org/W2962904108","https://openalex.org/W2962975498","https://openalex.org/W2963485453","https://openalex.org/W2963695795","https://openalex.org/W2964015378","https://openalex.org/W2964268978","https://openalex.org/W3004056434","https://openalex.org/W3100848837","https://openalex.org/W3104097132","https://openalex.org/W3105705953","https://openalex.org/W4289389616","https://openalex.org/W4294170691","https://openalex.org/W4294558607","https://openalex.org/W4297733535","https://openalex.org/W4320013936","https://openalex.org/W6631190155","https://openalex.org/W6636774829","https://openalex.org/W6677656871","https://openalex.org/W6682691769","https://openalex.org/W6683204974","https://openalex.org/W6726873649","https://openalex.org/W6738964360","https://openalex.org/W6748799445","https://openalex.org/W6755863455","https://openalex.org/W6756633790","https://openalex.org/W6757374366","https://openalex.org/W6762828668","https://openalex.org/W6773084841"],"related_works":["https://openalex.org/W2081900870","https://openalex.org/W4293226380","https://openalex.org/W2345479200","https://openalex.org/W2183306018","https://openalex.org/W2849310602","https://openalex.org/W3006008237","https://openalex.org/W4321487865","https://openalex.org/W2419146053","https://openalex.org/W4388890789","https://openalex.org/W4285218279"],"abstract_inverted_index":{"Network":[0],"representation":[1],"learning":[2,42,76,171],"(NRL)":[3],"has":[4,211],"far-reaching":[5],"effects":[6],"on":[7,77,119,189],"data":[8,51],"mining":[9],"research,":[10],"showing":[11],"its":[12,99,105],"importance":[13],"in":[14,29,70],"many":[15],"real-world":[16],"applications.":[17],"NRL,":[18],"also":[19],"known":[20],"as":[21,45,141],"network":[22,56],"embedding,":[23],"aims":[24],"at":[25],"preserving":[26],"graph":[27,54],"structures":[28],"a":[30,63,92,114,202,212],"low-dimensional":[31],"space.":[32],"These":[33],"learned":[34],"representations":[35],"can":[36,246],"be":[37,96,129],"used":[38],"for":[39,67,88,185],"subsequent":[40],"machine":[41],"tasks,":[43],"such":[44],"vertex":[46,94,163,216],"classification,":[47],"link":[48],"prediction,":[49],"and":[50,160,207],"visualization.":[52],"Recently,":[53],"convolutional":[55],"(GCN)-based":[57],"models,":[58],"e.g.,":[59],"GraphSAGE,":[60],"have":[61],"drawn":[62],"lot":[64],"of":[65,81,122,147,155,196,215],"attention":[66],"their":[68,236],"success":[69],"inductive":[71,187],"NRL.":[72],"When":[73],"conducting":[74],"unsupervised":[75,186],"large-scale":[78],"graphs,":[79],"some":[80],"these":[82,176],"models":[83,232],"employ":[84],"negative":[85,106,111,158,198],"sampling":[86,206],"(NS)":[87],"optimization,":[89],"which":[90,167],"encourages":[91],"target":[93,138,162],"to":[95,98,136,170,228],"close":[97],"neighbors":[100],"while":[101,218],"being":[102],"far":[103],"from":[104],"samples.":[107],"However,":[108],"NS":[109,148],"draws":[110],"vertices":[112],"through":[113],"random":[115],"pattern":[116],"or":[117,133],"based":[118],"the":[120,125,137,142,145,152,156,161,223,252],"degrees":[121],"vertices.":[123],"Thus,":[124],"generated":[126],"samples":[127,159],"could":[128],"either":[130],"highly":[131],"relevant":[132],"completely":[134],"unrelated":[135,157],"vertex.":[139],"Moreover,":[140],"training":[143,182,220],"goes,":[144],"gradient":[146],"objective":[149],"calculated":[150],"with":[151,205,251],"inner":[153],"product":[154],"may":[164],"become":[165],"zero,":[166],"will":[168],"lead":[169],"inferior":[172],"representations.":[173],"To":[174],"address":[175],"problems,":[177],"we":[178,200],"propose":[179],"an":[180],"adversarial":[181],"method":[183,225,245],"tailored":[184],"NRL":[188],"large":[190],"networks.":[191],"For":[192],"efficiently":[193],"keeping":[194],"track":[195],"high-quality":[197],"samples,":[199],"design":[201],"caching":[203],"scheme":[204],"updating":[208],"strategies":[209],"that":[210,242],"wide":[213],"exploration":[214],"proximity":[217],"considering":[219],"costs.":[221],"Besides,":[222],"proposed":[224,244],"is":[226],"adaptive":[227],"various":[229],"existing":[230],"GCN-based":[231],"without":[233],"significantly":[234],"complicating":[235],"optimization":[237],"process.":[238],"Extensive":[239],"experiments":[240],"show":[241],"our":[243],"achieve":[247],"better":[248],"performance":[249],"compared":[250],"state-of-the-art":[253],"models.":[254]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":4}],"updated_date":"2026-05-22T09:01:20.584952","created_date":"2025-10-10T00:00:00"}