{"id":"https://openalex.org/W4391853848","doi":"https://doi.org/10.1109/tkde.2024.3366396","title":"Semi-Supervised Graph Contrastive Learning With Virtual Adversarial Augmentation","display_name":"Semi-Supervised Graph Contrastive Learning With Virtual Adversarial Augmentation","publication_year":2024,"publication_date":"2024-02-15","ids":{"openalex":"https://openalex.org/W4391853848","doi":"https://doi.org/10.1109/tkde.2024.3366396"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2024.3366396","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2024.3366396","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Knowledge and Data Engineering","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"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/A5090734434","display_name":"Yixiang Dong","orcid":"https://orcid.org/0000-0001-8355-7282"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yixiang Dong","raw_affiliation_strings":["School of Computer Science and Technology, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013911439","display_name":"Minnan Luo","orcid":"https://orcid.org/0000-0002-0140-7860"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Minnan Luo","raw_affiliation_strings":["School of Computer Science and Technology, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029588473","display_name":"Jundong Li","orcid":"https://orcid.org/0000-0002-1878-817X"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jundong Li","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Department of Computer Science, University of Virginia, Charlottesville, VA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Department of Computer Science, University of Virginia, Charlottesville, VA, USA","institution_ids":["https://openalex.org/I51556381"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114860377","display_name":"Ziqi Liu","orcid":"https://orcid.org/0000-0002-4112-3504"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ziqi Liu","raw_affiliation_strings":["AI Department, Ant Group, Hangzhou, Zhejiang, China"],"affiliations":[{"raw_affiliation_string":"AI Department, Ant Group, Hangzhou, Zhejiang, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041083459","display_name":"Qinghua Zheng","orcid":"https://orcid.org/0000-0002-8436-4754"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qinghua Zheng","raw_affiliation_strings":["School of Computer Science and Technology, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I87445476"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5090734434"],"corresponding_institution_ids":["https://openalex.org/I87445476"],"apc_list":null,"apc_paid":null,"fwci":0.9971,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.74760262,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"36","issue":"8","first_page":"4232","last_page":"4244"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.928600013256073,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10057","display_name":"Face and Expression Recognition","score":0.928600013256073,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T12676","display_name":"Machine Learning and ELM","score":0.9190999865531921,"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":0.8075006604194641},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.706930935382843},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5334427952766418},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.48792359232902527},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.43545931577682495},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3396000266075134},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3127981126308441}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8075006604194641},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.706930935382843},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5334427952766418},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.48792359232902527},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.43545931577682495},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3396000266075134},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3127981126308441}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2024.3366396","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2024.3366396","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Knowledge and Data Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2172843688","display_name":null,"funder_award_id":"62250009","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4303215675","display_name":null,"funder_award_id":"62192781","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4896784468","display_name":null,"funder_award_id":"62137002","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4985986209","display_name":null,"funder_award_id":"62272374","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8740505804","display_name":null,"funder_award_id":"62202367","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/F4320330193","display_name":"Chinese Academy of Engineering","ror":"https://ror.org/00z3yke57"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W4246396837","https://openalex.org/W2482350142","https://openalex.org/W3176240006","https://openalex.org/W3126451824","https://openalex.org/W1561927205","https://openalex.org/W3191453585","https://openalex.org/W4297672492","https://openalex.org/W4288019534","https://openalex.org/W4310988119"],"abstract_inverted_index":{"Semi-supervised":[0],"graph":[1],"learning":[2,6,109,128],"aims":[3],"to":[4,50,130,149,174],"improve":[5,51],"performance":[7],"by":[8],"leveraging":[9],"unlabeled":[10,29,48],"nodes.":[11],"Typically,":[12],"it":[13],"can":[14,89],"be":[15],"approached":[16],"in":[17,61,120],"two":[18],"different":[19],"ways,":[20],"including":[21],"<italic":[22,37,138,165],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[23,38,139,166],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">predictive":[24],"representation":[25,142,156],"learning</i>":[26,143],"(PRL)":[27],"where":[28],"data":[30,86],"provide":[31],"clues":[32],"on":[33,110,181],"input":[34,151],"distribution":[35,46],"and":[36,84,92,114,118,198],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">label-dependent":[39],"regularization</i>":[40],"(LDR)":[41],"which":[42,112],"smooths":[43],"the":[44,94,131],"output":[45],"with":[47,145,171],"nodes":[49,152],"generalization.":[52],"However,":[53],"most":[54],"existing":[55],"PRL":[56,117],"approaches":[57],"suffer":[58],"from":[59],"overfitting":[60],"an":[62],"end-to-end":[63],"setting":[64],"or":[65],"cannot":[66],"encode":[67],"task-specific":[68],"information":[69],"when":[70],"used":[71],"as":[72],"unsupervised":[73],"pre-training":[74],"(i.e.,":[75],"two-stage":[76],"learning).":[77],"Meanwhile,":[78],"LDR":[79,119],"strategies":[80],"often":[81],"introduce":[82,163],"redundant":[83],"invalid":[85],"perturbations":[87,173],"that":[88,189],"slow":[90],"down":[91],"mislead":[93],"training.":[95],"To":[96],"address":[97],"all":[98],"these":[99],"issues,":[100],"we":[101,134],"propose":[102],"a":[103,121,126,137,154,164],"general":[104],"framework":[105],"SemiGraL":[106,190],"for":[107],"semi-supervised":[108,132,183],"graphs,":[111],"bridges":[113],"facilitates":[115],"both":[116],"single":[122],"shot.":[123],"By":[124],"extending":[125],"contrastive":[127,141],"architecture":[129],"setting,":[133],"first":[135],"develop":[136],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">semi-supervised":[140],"process":[144,170],"virtual":[146],"adversarial":[147],"augmentation":[148],"map":[150],"into":[153],"label-preserving":[155],"space":[157],"while":[158,194],"avoiding":[159],"overfitting.":[160],"We":[161],"then":[162],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">multiview":[167],"consistency":[168],"classification</i>":[169],"well-constrained":[172],"achieve":[175],"adversarially":[176],"robust":[177],"classification.":[178],"Extensive":[179],"experiments":[180],"seven":[182],"node":[184],"classification":[185],"benchmark":[186],"datasets":[187],"show":[188],"outperforms":[191],"various":[192],"baselines":[193],"enjoying":[195],"strong":[196],"generalization":[197],"robustness":[199],"performance.":[200]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
