{"id":"https://openalex.org/W4387968977","doi":"https://doi.org/10.1145/3581783.3611991","title":"Semi-supervised Domain Adaptation via Joint Contrastive Learning with Sensitivity","display_name":"Semi-supervised Domain Adaptation via Joint Contrastive Learning with Sensitivity","publication_year":2023,"publication_date":"2023-10-26","ids":{"openalex":"https://openalex.org/W4387968977","doi":"https://doi.org/10.1145/3581783.3611991"},"language":"en","primary_location":{"id":"doi:10.1145/3581783.3611991","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3581783.3611991","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Multimedia","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/A5033245187","display_name":"Keyu Tu","orcid":null},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Keyu Tu","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100376572","display_name":"Zilei Wang","orcid":"https://orcid.org/0000-0003-1822-3731"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zilei Wang","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101870242","display_name":"Junjie Li","orcid":"https://orcid.org/0000-0002-2906-8514"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junjie Li","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087744564","display_name":"Yixin Zhang","orcid":"https://orcid.org/0000-0002-4513-1106"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yixin Zhang","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5033245187"],"corresponding_institution_ids":["https://openalex.org/I126520041"],"apc_list":null,"apc_paid":null,"fwci":0.1725,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.57809784,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"5645","last_page":"5654"},"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":0.9664000272750854,"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/T10515","display_name":"Cancer-related molecular mechanisms research","score":0.9158999919891357,"subfield":{"id":"https://openalex.org/subfields/1306","display_name":"Cancer Research"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7784950733184814},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.7691178321838379},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7232227921485901},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6613178253173828},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5547352433204651},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5438261032104492},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.5373114347457886},{"id":"https://openalex.org/keywords/extractor","display_name":"Extractor","score":0.5343887805938721},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4867270290851593},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32062828540802}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7784950733184814},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.7691178321838379},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7232227921485901},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6613178253173828},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5547352433204651},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5438261032104492},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.5373114347457886},{"id":"https://openalex.org/C117978034","wikidata":"https://www.wikidata.org/wiki/Q5422192","display_name":"Extractor","level":2,"score":0.5343887805938721},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4867270290851593},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32062828540802},{"id":"https://openalex.org/C21880701","wikidata":"https://www.wikidata.org/wiki/Q2144042","display_name":"Process engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3581783.3611991","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3581783.3611991","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.5699999928474426,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G1231421488","display_name":null,"funder_award_id":"under","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G130652162","display_name":null,"funder_award_id":"202304","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2376276132","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G391238517","display_name":null,"funder_award_id":", and","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4150153631","display_name":null,"funder_award_id":"61836008","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5168046413","display_name":null,"funder_award_id":"62176246","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5616351183","display_name":null,"funder_award_id":"00000","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G566643046","display_name":null,"funder_award_id":"WK3490000006","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6241311946","display_name":null,"funder_award_id":"WK3490000006","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6844051781","display_name":null,"funder_award_id":"00000","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G8951484681","display_name":null,"funder_award_id":"Grant","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W2108598243","https://openalex.org/W2187089797","https://openalex.org/W2194775991","https://openalex.org/W2604319603","https://openalex.org/W2604587608","https://openalex.org/W2618530766","https://openalex.org/W2627183927","https://openalex.org/W2889240504","https://openalex.org/W2979579363","https://openalex.org/W2981720610","https://openalex.org/W2986381065","https://openalex.org/W2999905431","https://openalex.org/W3034562924","https://openalex.org/W3035510274","https://openalex.org/W3035524453","https://openalex.org/W3035682985","https://openalex.org/W3096541549","https://openalex.org/W3106895564","https://openalex.org/W3108655343","https://openalex.org/W3110080985","https://openalex.org/W3145450063","https://openalex.org/W3171007011","https://openalex.org/W3173682724","https://openalex.org/W3175593095","https://openalex.org/W3176720610","https://openalex.org/W3190654993","https://openalex.org/W3197393979","https://openalex.org/W3216298502","https://openalex.org/W4221162144","https://openalex.org/W4287110655","https://openalex.org/W4312365002","https://openalex.org/W6600018615","https://openalex.org/W6600617704"],"related_works":["https://openalex.org/W3080655457","https://openalex.org/W3166286441","https://openalex.org/W3214142563","https://openalex.org/W2945706271","https://openalex.org/W4387435415","https://openalex.org/W3136267388","https://openalex.org/W3186065094","https://openalex.org/W4287263085","https://openalex.org/W3093803318","https://openalex.org/W3204418343"],"abstract_inverted_index":{"Semi-supervised":[0],"Domain":[1],"Adaptation":[2],"(SSDA)":[3],"aims":[4],"to":[5,26,127,156,161,180],"learn":[6],"a":[7,92,188],"well-performed":[8,189],"model":[9],"using":[10],"fully":[11],"labeled":[12,17,31],"source":[13,35,52,72,167],"samples":[14,32,65,130,143],"and":[15,45,111,136,168,183,186,198,201],"scarcely":[16],"target":[18,23,64,85,169],"samples,":[19],"along":[20],"with":[21,97],"unlabeled":[22,142],"samples.":[24,170],"Due":[25],"the":[27,34,38,42,51,62,71,75,80,84,119,128,133,138,153,158,163,193,196,202],"dominant":[28],"presence":[29],"of":[30,83,105,141,166],"from":[33,70,118],"domain":[36],"in":[37,57,100,152],"training":[39],"data,":[40],"both":[41],"feature":[43,59,107,134,139],"extractor":[44],"classifier":[46,77,160],"can":[47,55,78,144],"display":[48],"bias":[49],"towards":[50],"domain.":[53,73,86],"This":[54],"result":[56],"sub-optimal":[58],"extraction":[60],"for":[61],"challenging":[63],"that":[66,205],"have":[67],"notable":[68],"differences":[69],"Moreover,":[74],"source-favored":[76],"hinder":[79],"classification":[81],"performance":[82],"To":[87],"this":[88,101],"end,":[89],"we":[90],"propose":[91],"novel":[93],"Joint":[94],"Contrastive":[95],"Learning":[96],"Sensitivity":[98],"(JCLS)":[99],"paper,":[102],"which":[103],"consists":[104],"sensitivity-aware":[106],"contrastive":[108,114,121,150],"learning":[109,115,151],"(SFCL)":[110],"class-wise":[112,149],"probabilistic":[113,154],"(CPCL).":[116],"Different":[117],"traditional":[120],"learning,":[122],"SFCL":[123],"pays":[124],"more":[125],"attention":[126],"sensitive":[129],"during":[131],"optimizing":[132],"extractor,":[135],"consequently":[137],"discrimination":[140],"be":[145],"enhanced.":[146],"CPCL":[147],"performs":[148],"space":[155],"enforce":[157],"cross-domain":[159],"match":[162],"real":[164],"distribution":[165],"By":[171],"combining":[172],"these":[173],"two":[174],"components,":[175],"our":[176,206],"JCLS":[177],"is":[178],"able":[179],"extract":[181],"domain-invariant":[182],"compact":[184],"features":[185],"obtain":[187],"classifier.":[190],"We":[191],"conduct":[192],"experiments":[194],"on":[195],"DomainNet":[197],"Office-Home":[199],"benchmarks,":[200],"results":[203],"show":[204],"approach":[207],"achieves":[208],"state-of-the-art":[209],"performance.":[210]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-04-13T07:58:08.660418","created_date":"2025-10-10T00:00:00"}