{"id":"https://openalex.org/W4414359918","doi":"https://doi.org/10.24963/ijcai.2025/219","title":"Gaussian Mixture Model for Graph Domain Adaptation","display_name":"Gaussian Mixture Model for Graph Domain Adaptation","publication_year":2025,"publication_date":"2025-09-01","ids":{"openalex":"https://openalex.org/W4414359918","doi":"https://doi.org/10.24963/ijcai.2025/219"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2025/219","is_oa":false,"landing_page_url":"https://doi.org/10.24963/ijcai.2025/219","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-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/A5101791332","display_name":"Mengzhu Wang","orcid":"https://orcid.org/0000-0002-8151-194X"},"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":"Mengzhu Wang","raw_affiliation_strings":["Hebei University of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hebei University of Technology","institution_ids":["https://openalex.org/I184843921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022557234","display_name":"Wenhao Ren","orcid":"https://orcid.org/0000-0002-8769-3131"},"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":"Wenhao Ren","raw_affiliation_strings":["Hebei University of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hebei University of Technology","institution_ids":["https://openalex.org/I184843921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101473492","display_name":"Yu Zhang","orcid":"https://orcid.org/0000-0001-8857-2801"},"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":"Yu Zhang","raw_affiliation_strings":["Hebei University of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hebei University of Technology","institution_ids":["https://openalex.org/I184843921"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yanlong Fan","orcid":null},"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":"Yanlong Fan","raw_affiliation_strings":["Hebei University of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hebei University of Technology","institution_ids":["https://openalex.org/I184843921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019758816","display_name":"Dianxi Shi","orcid":"https://orcid.org/0000-0002-8112-371X"},"institutions":[{"id":"https://openalex.org/I4210165407","display_name":"Intelligent Decision Systems (Spain)","ror":"https://ror.org/05xp52m23","country_code":"ES","type":"company","lineage":["https://openalex.org/I4210165407"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Dianxi Shi","raw_affiliation_strings":["Intelligent Game and Decision Lab (IGDL)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intelligent Game and Decision Lab (IGDL)","institution_ids":["https://openalex.org/I4210165407"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080392501","display_name":"Luoxi Jing","orcid":"https://orcid.org/0000-0002-1540-5815"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Luoxi Jing","raw_affiliation_strings":["Peking University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112114244","display_name":"Nan Yin","orcid":"https://orcid.org/0000-0002-9792-6066"},"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":"Nan Yin","raw_affiliation_strings":["Hong Kong University of Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hong Kong University of Science and Technology","institution_ids":["https://openalex.org/I200769079"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.7588,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.88626551,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1963","last_page":"1972"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.65829998254776,"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/T12676","display_name":"Machine Learning and ELM","score":0.65829998254776,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.640999972820282,"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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.600600004196167,"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/mixture-model","display_name":"Mixture model","score":0.8445000052452087},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.6262000203132629},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6166999936103821},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5803999900817871},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.569599986076355},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5602999925613403},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4950000047683716},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.46799999475479126},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.42010000348091125},{"id":"https://openalex.org/keywords/gaussian-network-model","display_name":"Gaussian network model","score":0.38119998574256897}],"concepts":[{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.8445000052452087},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6266999840736389},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.6262000203132629},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6166999936103821},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5803999900817871},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.569599986076355},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5602999925613403},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5450999736785889},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4950000047683716},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.46799999475479126},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.42010000348091125},{"id":"https://openalex.org/C166550679","wikidata":"https://www.wikidata.org/wiki/Q263400","display_name":"Gaussian network model","level":3,"score":0.38119998574256897},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.3677999973297119},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3594000041484833},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3538999855518341},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34850001335144043},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.3447999954223633},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.34380000829696655},{"id":"https://openalex.org/C92548554","wikidata":"https://www.wikidata.org/wiki/Q2262868","display_name":"Domain model","level":3,"score":0.32829999923706055},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.3237000107765198},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.321399986743927},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.301800012588501},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.29899999499320984},{"id":"https://openalex.org/C101814296","wikidata":"https://www.wikidata.org/wiki/Q5439685","display_name":"Feature model","level":3,"score":0.2915000021457672},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.27149999141693115},{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.2676999866962433},{"id":"https://openalex.org/C7218915","wikidata":"https://www.wikidata.org/wiki/Q1054475","display_name":"Gaussian function","level":3,"score":0.2662999927997589},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.262800008058548},{"id":"https://openalex.org/C2779736610","wikidata":"https://www.wikidata.org/wiki/Q6884140","display_name":"Mixture theory","level":3,"score":0.2621000111103058},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2603999972343445},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.2603999972343445},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.25440001487731934},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.25130000710487366}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2025/219","is_oa":false,"landing_page_url":"https://doi.org/10.24963/ijcai.2025/219","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Unsupervised":[0],"domain":[1,18,94,185],"adaptation":[2,95,186],"(UDA)":[3],"has":[4],"been":[5],"widely":[6],"studied":[7],"with":[8],"the":[9,33,37,51,54,65,101,105,112,121,126,129,133,140,145,151,158,178],"goal":[10],"of":[11,125,132,153,190],"transferring":[12],"knowledge":[13],"from":[14],"a":[15,20,74,87,116,163],"label-rich":[16],"source":[17,55,106,146],"to":[19,40,67,137,161],"related":[21],"but":[22],"unlabeled":[23],"target":[24,57,108,148],"domain.":[25],"Most":[26],"UDA":[27],"techniques":[28],"achieve":[29],"this":[30,82,84,156],"by":[31,110],"reducing":[32],"feature":[34,43,47],"discrepancies":[35],"between":[36,53,104,144],"two":[38],"domains":[39,109],"learn":[41,139],"domain-invariant":[42,46],"representations.":[44],"While":[45],"representations":[48],"can":[49],"reduce":[50],"differences":[52,62,114],"and":[56,107,128,147],"domains,":[58],"excessively":[59],"simplifying":[60],"these":[61],"may":[63],"cause":[64],"model":[66,98,136,166],"overlook":[68],"important":[69],"domain-specific":[70],"features,":[71],"resulting":[72],"in":[73,76,188],"decline":[75],"transfer":[77],"learning":[78],"effectiveness.":[79],"To":[80,150],"address":[81],"issue,":[83],"paper":[85],"proposes":[86],"novel":[88],"Gaussian":[89,134,164],"Mixture":[90],"Model":[91],"for":[92],"graph":[93,117,127],"(GMM).":[96],"This":[97],"effectively":[99],"reduces":[100],"distributional":[102],"bias":[103],"modeling":[111],"distribution":[113],"on":[115,172],"structure.":[118],"GMM":[119,180],"leverages":[120],"local":[122],"structural":[123],"information":[124],"clustering":[130],"capability":[131],"mixture":[135,165],"automatically":[138],"latent":[141],"mapping":[142],"relationships":[143],"domains.":[149],"best":[152],"our":[154],"knowledge,":[155],"is":[157],"first":[159],"work":[160],"introduce":[162],"into":[167],"UDA.":[168],"Extensive":[169],"experimental":[170],"results":[171],"three":[173],"standard":[174],"benchmarks":[175],"demonstrate":[176],"that":[177],"proposed":[179],"algorithm":[181],"outperforms":[182],"state-of-the-art":[183],"unsupervised":[184],"methods":[187],"terms":[189],"performance.":[191]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
