{"id":"https://openalex.org/W4304084069","doi":"https://doi.org/10.1145/3503161.3548059","title":"Label-Efficient Domain Generalization via Collaborative Exploration and Generalization","display_name":"Label-Efficient Domain Generalization via Collaborative Exploration and Generalization","publication_year":2022,"publication_date":"2022-10-10","ids":{"openalex":"https://openalex.org/W4304084069","doi":"https://doi.org/10.1145/3503161.3548059"},"language":"en","primary_location":{"id":"doi:10.1145/3503161.3548059","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3503161.3548059","pdf_url":null,"source":{"id":"https://openalex.org/S4363608757","display_name":"Proceedings of the 30th ACM International Conference on Multimedia","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"conference-paper","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/A5049344673","display_name":"Junkun Yuan","orcid":"https://orcid.org/0000-0003-0012-7397"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junkun Yuan","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100701889","display_name":"Xu Ma","orcid":"https://orcid.org/0000-0003-2864-4708"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu Ma","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101821806","display_name":"Defang Chen","orcid":"https://orcid.org/0000-0003-0833-7401"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Defang Chen","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041727387","display_name":"Kun Kuang","orcid":"https://orcid.org/0000-0001-7024-9790"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kun Kuang","raw_affiliation_strings":["Zhejiang University &amp; Shanghai AI Laboratory, Hangzhou &amp; Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University &amp; Shanghai AI Laboratory, Hangzhou &amp; Shanghai, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004882141","display_name":"Fei Wu","orcid":"https://orcid.org/0000-0003-2139-8807"},"institutions":[{"id":"https://openalex.org/I4210111959","display_name":"Shanghai Advanced Research Institute","ror":"https://ror.org/02br7py06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210111959"]},{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fei Wu","raw_affiliation_strings":["Zhejiang University &amp; Shanghai Institute for Advanced Study of Zhejiang University, Hangzhou &amp; Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University &amp; Shanghai Institute for Advanced Study of Zhejiang University, Hangzhou &amp; Shanghai, China","institution_ids":["https://openalex.org/I4210111959","https://openalex.org/I76130692"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090814258","display_name":"Lanfen Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lanfen Lin","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.2051,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.93544086,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"2361","last_page":"2370"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9997000098228455,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9997000098228455,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9894999861717224,"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/T11243","display_name":"Respiratory viral infections research","score":0.9337000250816345,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.760615348815918},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.7062007188796997},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5946126580238342},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5581508278846741},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.5410977005958557},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.5070655345916748},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4395570456981659},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to rank","score":0.43655213713645935},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.3490535020828247},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12668287754058838}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.760615348815918},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.7062007188796997},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5946126580238342},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5581508278846741},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.5410977005958557},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.5070655345916748},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4395570456981659},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.43655213713645935},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.3490535020828247},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12668287754058838},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3503161.3548059","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3503161.3548059","pdf_url":null,"source":{"id":"https://openalex.org/S4363608757","display_name":"Proceedings of the 30th ACM International Conference on Multimedia","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.6399999856948853}],"awards":[{"id":"https://openalex.org/G4226697956","display_name":null,"funder_award_id":"62006207,62037001","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5417803145","display_name":"\u57fa\u4e8e\u8054\u90a6\u5b66\u4e60\u7684\u672f\u524dHCC \u65e9\u671f\u590d\u53d1\u68c0\u6d4b\u9884\u6d4b","funder_award_id":"LZ22F020012","funder_id":"https://openalex.org/F4320338464","funder_display_name":"Natural Science Foundation of Zhejiang Province"},{"id":"https://openalex.org/G6068693748","display_name":null,"funder_award_id":"2021YFC3340300","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program 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},{"id":"https://openalex.org/F4320338464","display_name":"Natural Science Foundation of Zhejiang Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W2124244761","https://openalex.org/W2126151240","https://openalex.org/W2162651021","https://openalex.org/W2187089797","https://openalex.org/W2194775991","https://openalex.org/W2627183927","https://openalex.org/W2763549966","https://openalex.org/W2798658180","https://openalex.org/W2807992610","https://openalex.org/W2889965839","https://openalex.org/W2949736877","https://openalex.org/W2963043696","https://openalex.org/W2970119729","https://openalex.org/W2990138404","https://openalex.org/W2997591099","https://openalex.org/W2997746169","https://openalex.org/W2998712190","https://openalex.org/W3011304563","https://openalex.org/W3021496598","https://openalex.org/W3034373371","https://openalex.org/W3156216502","https://openalex.org/W3172509117","https://openalex.org/W3173329083","https://openalex.org/W3173908982","https://openalex.org/W3179550234","https://openalex.org/W3180439858","https://openalex.org/W3183864931","https://openalex.org/W3184966323","https://openalex.org/W3190096330","https://openalex.org/W3190960741","https://openalex.org/W3201074629","https://openalex.org/W3205572132","https://openalex.org/W3205799947","https://openalex.org/W3206271621","https://openalex.org/W3206487064","https://openalex.org/W3206525885","https://openalex.org/W3206776650","https://openalex.org/W3207727708","https://openalex.org/W3207856632","https://openalex.org/W3207977952","https://openalex.org/W4205616158","https://openalex.org/W4221141639","https://openalex.org/W4249502209","https://openalex.org/W4255556797","https://openalex.org/W4285345657","https://openalex.org/W4304091498","https://openalex.org/W6600617704"],"related_works":["https://openalex.org/W3127142483","https://openalex.org/W4385565564","https://openalex.org/W2898073868","https://openalex.org/W2138488530","https://openalex.org/W4390446658","https://openalex.org/W3089100822","https://openalex.org/W2971071571","https://openalex.org/W2798835721","https://openalex.org/W2387658907","https://openalex.org/W2922169395"],"abstract_inverted_index":{"Considerable":[0],"progress":[1],"has":[2],"been":[3],"made":[4],"in":[5,38,53,99,160],"domain":[6,48,63,106,129,147,151],"generalization":[7,49,64,69,159,172,183],"(DG)":[8],"which":[9,90],"aims":[10],"to":[11,21,31,66,102,145,196,201],"learn":[12],"a":[13,58,81,161],"generalizable":[14],"model":[15,68,171],"from":[16,44],"multiple":[17],"well-annotated":[18],"source":[19,36,72],"domains":[20],"unknown":[22],"target":[23],"domains.":[24,73],"However,":[25],"it":[26],"can":[27,188],"be":[28],"prohibitively":[29],"expensive":[30],"obtain":[32],"sufficient":[33],"annotation":[34,51,194],"for":[35],"datasets":[37],"many":[39],"real":[40],"scenarios.":[41],"To":[42,74],"escape":[43],"the":[45,116,119,122,202],"dilemma":[46],"between":[47,168],"and":[50,87,95,105,112,131,141,149,157,164],"costs,":[52],"this":[54,76],"paper,":[55],"we":[56,79,114,137],"introduce":[57],"novel":[59,82],"task":[60],"named":[61],"label-efficient":[62],"(LEDG)":[65],"enable":[67],"with":[70,121,173,206],"label-limited":[71],"address":[75],"challenging":[77],"task,":[78],"propose":[80],"framework":[83],"called":[84],"Collaborative":[85],"Exploration":[86],"Generalization":[88],"(CEG)":[89],"jointly":[91],"optimizes":[92],"active":[93,100,155],"exploration":[94,156],"semi-supervised":[96,135,158],"generalization.":[97],"Specifically,":[98],"exploration,":[101],"explore":[103],"class":[104,127],"discriminability":[107],"while":[108],"avoiding":[109],"information":[110,132],"divergence":[111],"redundancy,":[113],"query":[115],"labels":[117],"of":[118,126],"samples":[120],"highest":[123],"overall":[124],"ranking":[125],"uncertainty,":[128],"representativeness,":[130],"diversity.":[133],"In":[134,185],"generalization,":[136],"design":[138],"MixUp-based":[139],"intra-":[140],"inter-domain":[142],"knowledge":[143,148],"augmentation":[144],"expand":[146],"generalize":[150],"invariance.":[152],"We":[153],"unify":[154],"collaborative":[162],"way":[163],"promote":[165],"mutual":[166],"enhancement":[167],"them,":[169],"boosting":[170],"limited":[174],"annotation.":[175],"Extensive":[176],"experiments":[177],"show":[178],"that":[179],"CEG":[180,187],"yields":[181],"superior":[182],"performance.":[184],"particular,":[186],"even":[189],"use":[190],"only":[191],"5%":[192],"data":[193,209],"budget":[195],"achieve":[197],"competitive":[198],"results":[199],"compared":[200],"previous":[203],"DG":[204],"methods":[205],"fully":[207],"labeled":[208],"on":[210],"PACS":[211],"dataset.":[212]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
