{"id":"https://openalex.org/W4400910491","doi":"https://doi.org/10.1109/icde60146.2024.00095","title":"GradGCL: Gradient Graph Contrastive Learning","display_name":"GradGCL: Gradient Graph Contrastive Learning","publication_year":2024,"publication_date":"2024-05-13","ids":{"openalex":"https://openalex.org/W4400910491","doi":"https://doi.org/10.1109/icde60146.2024.00095"},"language":"en","primary_location":{"id":"doi:10.1109/icde60146.2024.00095","doi":"https://doi.org/10.1109/icde60146.2024.00095","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icde60146.2024.00095","pdf_url":null,"source":{"id":"https://openalex.org/S4210210321","display_name":"IEEE International Conference on Data Engineering (ICDE)","issn_l":"1084-4627","issn":["1084-4627","2375-0286"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","norway-2"],"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 40th International Conference on Data Engineering (ICDE)","raw_type":"proceedings-article"},"parent_works":[],"lineage":["https://openalex.org/W4400910491"],"child_works_count":0,"type":"conference-paper","is_traditional":true,"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/A5068273853","display_name":"Ran Li","orcid":"https://orcid.org/0000-0002-5034-7294","observed_orcids":["https://orcid.org/0000-0002-5034-7294"]},"institutions":[{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Ran Li","raw_affiliation_strings":["The Hong Kong University of Science and Technology,Hong Kong SAR,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Hong Kong University of Science and Technology,Hong Kong SAR,China","institution_ids":["https://openalex.org/I200769079"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006260400","display_name":"Shimin Di","orcid":"https://orcid.org/0000-0002-7394-0082","observed_orcids":["https://orcid.org/0000-0002-7394-0082"]},"institutions":[{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Shimin Di","raw_affiliation_strings":["The Hong Kong University of Science and Technology,Hong Kong SAR,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Hong Kong University of Science and Technology,Hong Kong SAR,China","institution_ids":["https://openalex.org/I200769079"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100333516","display_name":"Lei Chen","orcid":"https://orcid.org/0000-0002-8257-5806","observed_orcids":["https://orcid.org/0000-0002-8257-5806","https://orcid.org/0000-0002-1054-5501","https://orcid.org/0000-0002-4912-3293","https://orcid.org/0000-0002-7918-8936","https://orcid.org/0000-0003-4664-0700"]},"institutions":[{"id":"https://openalex.org/I4405261251","display_name":"The Hong Kong University of Science and Technology (Guangzhou)","ror":"https://ror.org/050h0vm43","country_code":"CN","type":"education","lineage":["https://openalex.org/I4405261251"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Chen","raw_affiliation_strings":["The Hong Kong University of Science and Technology (Guangzhou),Guangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Hong Kong University of Science and Technology (Guangzhou),Guangzhou,China","institution_ids":["https://openalex.org/I4405261251"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011384237","display_name":"Xiaofang Zhou","orcid":"https://orcid.org/0000-0001-6343-1455","observed_orcids":["https://orcid.org/0000-0001-6343-1455","https://orcid.org/0000-0001-5878-3683"]},"institutions":[{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Xiaofang Zhou","raw_affiliation_strings":["The Hong Kong University of Science and Technology,Hong Kong SAR,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Hong Kong University of Science and Technology,Hong Kong SAR,China","institution_ids":["https://openalex.org/I200769079"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4581,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.61274295,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1171","last_page":"1184"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":1.0,"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":1.0,"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/T12292","display_name":"Graph Theory and Algorithms","score":0.0,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T10057","display_name":"Face and Expression Recognition","score":0.0,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/graph-contrastive-learning","display_name":"graph contrastive learning","score":0.9539999961853027},{"id":"https://openalex.org/keywords/graph-self-supervised-learning","display_name":"graph self-supervised learning","score":0.8889999985694885},{"id":"https://openalex.org/keywords/gradient-information","display_name":"gradient information","score":0.7170000076293945},{"id":"https://openalex.org/keywords/dimensional-collapse","display_name":"dimensional collapse","score":0.7440000176429749},{"id":"https://openalex.org/keywords/representation-diversity","display_name":"representation diversity","score":0.609000027179718},{"id":"https://openalex.org/keywords/graph-representation-learning","display_name":"graph representation learning","score":0.7689999938011169},{"id":"https://openalex.org/keywords/contrastive-loss","display_name":"contrastive loss","score":0.5759999752044678}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6989156007766724},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4958425462245941},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.49381980299949646},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.39297980070114136},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.25858038663864136}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icde60146.2024.00095","doi":"https://doi.org/10.1109/icde60146.2024.00095","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icde60146.2024.00095","pdf_url":null,"source":{"id":"https://openalex.org/S4210210321","display_name":"IEEE International Conference on Data Engineering (ICDE)","issn_l":"1084-4627","issn":["1084-4627","2375-0286"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","norway-2"],"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 40th International Conference on Data Engineering (ICDE)","raw_type":"proceedings-article"},{"id":"pmh:oai:repository.hkust.edu.hk:1783.1-137234","doi":null,"is_oa":false,"landing_page_url":"http://repository.hkust.edu.hk/ir/Record/1783.1-137234","pdf_url":null,"source":{"id":"https://openalex.org/S4306401796","display_name":"Rare & Special e-Zone (The Hong Kong University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I200769079","host_organization_name":"Hong Kong University of Science and Technology","host_organization_lineage":["https://openalex.org/I200769079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference paper"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":74,"referenced_works":["https://openalex.org/W1492230849","https://openalex.org/W1757990252","https://openalex.org/W1849277567","https://openalex.org/W2008857988","https://openalex.org/W2046084401","https://openalex.org/W2092750499","https://openalex.org/W2138621090","https://openalex.org/W2142498761","https://openalex.org/W2519887557","https://openalex.org/W2523246573","https://openalex.org/W2525739395","https://openalex.org/W2554952599","https://openalex.org/W2594183968","https://openalex.org/W2737925311","https://openalex.org/W2767404761","https://openalex.org/W2808409763","https://openalex.org/W2808803559","https://openalex.org/W2887997457","https://openalex.org/W2894175828","https://openalex.org/W2896457183","https://openalex.org/W2919115771","https://openalex.org/W2950411297","https://openalex.org/W2951922582","https://openalex.org/W2962756421","https://openalex.org/W2962858109","https://openalex.org/W2963341956","https://openalex.org/W2965556524","https://openalex.org/W2970971581","https://openalex.org/W2995060963","https://openalex.org/W2996604169","https://openalex.org/W3005680577","https://openalex.org/W3009561768","https://openalex.org/W3010723741","https://openalex.org/W3021975806","https://openalex.org/W3027758526","https://openalex.org/W3033039844","https://openalex.org/W3034693603","https://openalex.org/W3042313988","https://openalex.org/W3042850010","https://openalex.org/W3080997787","https://openalex.org/W3095746859","https://openalex.org/W3097606775","https://openalex.org/W3101620381","https://openalex.org/W3102419180","https://openalex.org/W3114632476","https://openalex.org/W3127035078","https://openalex.org/W3132402977","https://openalex.org/W3133849783","https://openalex.org/W3134210100","https://openalex.org/W3156306687","https://openalex.org/W3167553825","https://openalex.org/W3205065023","https://openalex.org/W3211399938","https://openalex.org/W4221023051","https://openalex.org/W4226002507","https://openalex.org/W4283065718","https://openalex.org/W4289533750","https://openalex.org/W4289533857","https://openalex.org/W4289533979","https://openalex.org/W4290876361","https://openalex.org/W4290878031","https://openalex.org/W4297808394","https://openalex.org/W4310895557","https://openalex.org/W4312929313","https://openalex.org/W4367047253","https://openalex.org/W4385270378","https://openalex.org/W4385282405","https://openalex.org/W4385567983","https://openalex.org/W4386591587","https://openalex.org/W4392367472","https://openalex.org/W4400909958","https://openalex.org/W6741450815","https://openalex.org/W6796435857","https://openalex.org/W7133228811"],"related_works":["https://openalex.org/W4391528757","https://openalex.org/W4394898073","https://openalex.org/W7134952193","https://openalex.org/W7167700517","https://openalex.org/W4321206894","https://openalex.org/W4390738999","https://openalex.org/W4392271129","https://openalex.org/W4402029607","https://openalex.org/W4296414197","https://openalex.org/W4416252274"],"abstract_inverted_index":{"Graph":[0],"self-supervised":[1],"learning":[2,22,38,50],"aiming":[3],"to":[4,31,113,129,154,170,178],"learn":[5,235],"the":[6,34,80,102,116,121,162,166,171,179,191,207,258],"graph":[7,25,48,117,126,236],"representation":[8,103,208],"without":[9],"much":[10],"label":[11],"information":[12,71,148,160,237],"is":[13,27],"an":[14,150],"important":[15],"tasks":[16],"in":[17,33,67,83,101,206],"data":[18,26,107,118],"mining":[19],"and":[20,29,72,94,119,123,131,197,204,226,238,256],"machine":[21],"since":[23],"labeled":[24],"scarce":[28],"expensive":[30],"obtain":[32],"real":[35],"world.":[36],"Contrastive":[37],"emerges":[39],"as":[40,149],"a":[41,54,63,68,106,141,175,185],"promising":[42],"solution.":[43],"However,":[44],"we":[45,138,182],"show":[46,248],"existing":[47,253],"contrastive":[49,172,223],"(GCL)":[51],"models":[52,255],"have":[53,183,211],"significant":[55],"issue:":[56],"they":[57],"generate":[58],"representations":[59,167],"that":[60,87,144,189,231,249],"collapse":[61],"into":[62],"low-dimensional":[64],"subspace,":[65],"resulting":[66],"loss":[69],"of":[70,125,165,222,260],"diversity.":[73],"We":[74,210,229,246],"believe":[75],"this":[76,110,136],"issue":[77,259],"arises":[78],"from":[79],"strong":[81],"assumption":[82,111],"current":[84],"GCL":[85,156,244,254],"methods":[86],"all":[88,95],"positive":[89,196],"samples":[90,97],"should":[91,98],"be":[92,99],"close":[93],"negative":[96,198],"far":[100],"space.":[104,209],"From":[105],"engineering":[108],"view,":[109],"fails":[112],"deeply":[114],"mine":[115],"oversimplifies":[120],"complexity":[122],"heterogeneity":[124],"data,":[127],"leading":[128],"clustered":[130],"redundant":[132],"representations.":[133,180],"To":[134],"address":[135],"issue,":[137],"propose":[139],"GradGCL,":[140],"novel":[142],"method":[143],"leverages":[145],"intrinsic":[146],"gradient":[147,159],"additional":[151],"input":[152],"signal":[153],"regularize":[155],"training.":[157],"The":[158],"reflects":[161],"optimization":[163],"process":[164],"with":[168,242],"respect":[169],"loss,":[173],"providing":[174],"complementary":[176],"perspective":[177],"Furthermore,":[181],"designed":[184],"soft":[186],"separation":[187,193],"strategy":[188,194],"relaxes":[190],"hard":[192],"between":[195],"samples,":[199],"allowing":[200],"for":[201],"more":[202],"flexibility":[203],"diversity":[205],"conducted":[212],"extensive":[213],"experiments":[214],"on":[215],"various":[216],"graph-related":[217],"tasks,":[218],"using":[219],"different":[220],"types":[221],"losses,":[224],"datasets,":[225],"model":[227],"architectures.":[228],"demonstrate":[230],"gradients":[232],"alone":[233],"can":[234,251],"achieve":[239],"competitive":[240],"results":[241],"representation-based":[243],"methods.":[245],"also":[247],"GradGCL":[250],"enhance":[252],"prevent":[257],"dimensional":[261],"collapse.":[262]},"counts_by_year":[{"year":2025,"cited_by_count":3}],"updated_date":"2026-11-13T13:42:25.865203","created_date":"2024-07-24T00:00:00"}