{"id":"https://openalex.org/W4401608728","doi":"https://doi.org/10.1109/tifs.2024.3444319","title":"ROSE: Relational and Prototypical Structure Learning for Universal Domain Adaptive Hashing","display_name":"ROSE: Relational and Prototypical Structure Learning for Universal Domain Adaptive Hashing","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4401608728","doi":"https://doi.org/10.1109/tifs.2024.3444319"},"language":"en","primary_location":{"id":"doi:10.1109/tifs.2024.3444319","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/tifs.2024.3444319","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"is_oa":false,"is_in_doaj":false,"is_core":true,"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":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Information Forensics and Security","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/A5083920026","display_name":"Xinlong Yang","orcid":"https://orcid.org/0000-0002-0835-8176"},"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":"Xinlong Yang","raw_affiliation_strings":["National Engineering and Research Center for Software Engineering, Peking University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-0835-8176","affiliations":[{"raw_affiliation_string":"National Engineering and Research Center for Software Engineering, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100617262","display_name":"Haixin Wang","orcid":"https://orcid.org/0000-0002-5714-0149"},"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":"Haixin Wang","raw_affiliation_strings":["National Engineering and Research Center for Software Engineering, Peking University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-5714-0149","affiliations":[{"raw_affiliation_string":"National Engineering and Research Center for Software Engineering, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072710764","display_name":"Jinan Sun","orcid":"https://orcid.org/0000-0001-8138-9262"},"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":"Jinan Sun","raw_affiliation_strings":["National Engineering and Research Center for Software Engineering, Peking University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-8138-9262","affiliations":[{"raw_affiliation_string":"National Engineering and Research Center for Software Engineering, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040226555","display_name":"Yijia Xiao","orcid":"https://orcid.org/0000-0002-5512-3070"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yijia Xiao","raw_affiliation_strings":["Department of Computer Science, University of California at Los Angeles, Los Angeles, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of California at Los Angeles, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001181973","display_name":"Wei Xiang","orcid":"https://orcid.org/0000-0001-5267-3184"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei Xiang","raw_affiliation_strings":["BIGO Ltd., Suntec Tower 3, Singapore"],"raw_orcid":"https://orcid.org/0000-0001-5267-3184","affiliations":[{"raw_affiliation_string":"BIGO Ltd., Suntec Tower 3, Singapore","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100348795","display_name":"Chong Chen","orcid":"https://orcid.org/0000-0003-0213-9957"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chong Chen","raw_affiliation_strings":["Terminus Group, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Terminus Group, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024965898","display_name":"Xian\u2010Sheng Hua","orcid":"https://orcid.org/0000-0002-8232-5049"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xian-Sheng Hua","raw_affiliation_strings":["Terminus Group, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-8232-5049","affiliations":[{"raw_affiliation_string":"Terminus Group, Beijing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100426938","display_name":"Xiao Luo","orcid":"https://orcid.org/0000-0002-7987-3714"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiao Luo","raw_affiliation_strings":["Department of Computer Science, University of California at Los Angeles, Los Angeles, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-7987-3714","affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of California at Los Angeles, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I161318765"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2401,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.6344251,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"19","issue":null,"first_page":"7690","last_page":"7704"},"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":0.9991000294685364,"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":0.9991000294685364,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9986000061035156,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9962999820709229,"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/computer-science","display_name":"Computer science","score":0.8124001026153564},{"id":"https://openalex.org/keywords/hash-function","display_name":"Hash function","score":0.6021572947502136},{"id":"https://openalex.org/keywords/universal-hashing","display_name":"Universal hashing","score":0.5229352712631226},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.47825682163238525},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44501224160194397},{"id":"https://openalex.org/keywords/relational-database","display_name":"Relational database","score":0.4115902781486511},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.410225510597229},{"id":"https://openalex.org/keywords/hash-table","display_name":"Hash table","score":0.29043203592300415},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.2193543016910553},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.17359310388565063},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10123240947723389},{"id":"https://openalex.org/keywords/double-hashing","display_name":"Double hashing","score":0.09971052408218384}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8124001026153564},{"id":"https://openalex.org/C99138194","wikidata":"https://www.wikidata.org/wiki/Q183427","display_name":"Hash function","level":2,"score":0.6021572947502136},{"id":"https://openalex.org/C116058348","wikidata":"https://www.wikidata.org/wiki/Q846912","display_name":"Universal hashing","level":5,"score":0.5229352712631226},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.47825682163238525},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44501224160194397},{"id":"https://openalex.org/C5655090","wikidata":"https://www.wikidata.org/wiki/Q192588","display_name":"Relational database","level":2,"score":0.4115902781486511},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.410225510597229},{"id":"https://openalex.org/C67388219","wikidata":"https://www.wikidata.org/wiki/Q207440","display_name":"Hash table","level":3,"score":0.29043203592300415},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2193543016910553},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.17359310388565063},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10123240947723389},{"id":"https://openalex.org/C138111711","wikidata":"https://www.wikidata.org/wiki/Q478351","display_name":"Double hashing","level":4,"score":0.09971052408218384},{"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:10.1109/tifs.2024.3444319","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/tifs.2024.3444319","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"is_oa":false,"is_in_doaj":false,"is_core":true,"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":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Information Forensics and Security","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":85,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1722318740","https://openalex.org/W1956333070","https://openalex.org/W2411707397","https://openalex.org/W2464915613","https://openalex.org/W2627183927","https://openalex.org/W2766280096","https://openalex.org/W2798702669","https://openalex.org/W2799245683","https://openalex.org/W2799787995","https://openalex.org/W2842511635","https://openalex.org/W2885018852","https://openalex.org/W2885722640","https://openalex.org/W2890032859","https://openalex.org/W2901389242","https://openalex.org/W2916781626","https://openalex.org/W2948069880","https://openalex.org/W2964158883","https://openalex.org/W2966088020","https://openalex.org/W2975761438","https://openalex.org/W3000097396","https://openalex.org/W3006871679","https://openalex.org/W3009806461","https://openalex.org/W3034239448","https://openalex.org/W3034315422","https://openalex.org/W3034779842","https://openalex.org/W3034971598","https://openalex.org/W3035524453","https://openalex.org/W3035732386","https://openalex.org/W3088877992","https://openalex.org/W3114063012","https://openalex.org/W3134162419","https://openalex.org/W3154887397","https://openalex.org/W3156173975","https://openalex.org/W3173956867","https://openalex.org/W3175328093","https://openalex.org/W3175562757","https://openalex.org/W3177151237","https://openalex.org/W3177391608","https://openalex.org/W3187985423","https://openalex.org/W3188087362","https://openalex.org/W3189423081","https://openalex.org/W3198680251","https://openalex.org/W3200012480","https://openalex.org/W3205692356","https://openalex.org/W3207182362","https://openalex.org/W3208886632","https://openalex.org/W3213646008","https://openalex.org/W4214604401","https://openalex.org/W4214671648","https://openalex.org/W4214697508","https://openalex.org/W4220673617","https://openalex.org/W4283804765","https://openalex.org/W4284708713","https://openalex.org/W4286372554","https://openalex.org/W4288049153","https://openalex.org/W4290874851","https://openalex.org/W4296437707","https://openalex.org/W4297808394","https://openalex.org/W4304083183","https://openalex.org/W4312335633","https://openalex.org/W4312496732","https://openalex.org/W4312627428","https://openalex.org/W4313034093","https://openalex.org/W4313069894","https://openalex.org/W4319878852","https://openalex.org/W4378696994","https://openalex.org/W4382407431","https://openalex.org/W4384519174","https://openalex.org/W4386065601","https://openalex.org/W4386076359","https://openalex.org/W4387968474","https://openalex.org/W4387968990","https://openalex.org/W4390874611","https://openalex.org/W4394597269","https://openalex.org/W6637373629","https://openalex.org/W6767375087","https://openalex.org/W6770196601","https://openalex.org/W6773005947","https://openalex.org/W6774314701","https://openalex.org/W6779997284","https://openalex.org/W6801929243","https://openalex.org/W6802035071","https://openalex.org/W6839849348","https://openalex.org/W6856607001"],"related_works":["https://openalex.org/W2132034299","https://openalex.org/W3124800526","https://openalex.org/W4251536634","https://openalex.org/W2088296667","https://openalex.org/W1551533237","https://openalex.org/W2185281229","https://openalex.org/W1750955152","https://openalex.org/W43986179","https://openalex.org/W4319653630","https://openalex.org/W3192973254"],"abstract_inverted_index":{"As":[0],"an":[1],"important":[2],"problem":[3,38,79],"in":[4,68,162,177],"searching":[5],"system":[6],"development,":[7],"domain":[8,28,63,82,92,115],"adaptive":[9,29,83],"retrieval":[10,15],"seeks":[11],"to":[12,35,66,107,113,158],"train":[13],"a":[14,75,99,119,201],"model":[16],"with":[17,39,143,174],"both":[18],"labeled":[19],"source":[20,46,208],"samples":[21,149],"and":[22,47,77,103],"unlabeled":[23],"target":[24,48,62,147,183],"samples.":[25],"Although":[26],"several":[27,192],"hashing":[30,100,160],"algorithms":[31],"have":[32],"been":[33],"proposed":[34,197],"handle":[36],"the":[37,57,61,88,109,133,137,153,163,178],"high":[40],"efficiency,":[41],"they":[42],"often":[43],"presume":[44],"that":[45,195],"domains":[49],"share":[50],"all":[51],"classes.":[52],"However,":[53],"prior":[54],"knowledge":[55],"about":[56],"label":[58,187],"space":[59],"on":[60,127,191],"is":[64,210],"hard":[65],"obtain":[67],"reality.":[69],"To":[70],"tackle":[71],"this,":[72],"we":[73,97,117,169],"study":[74],"novel":[76],"challenging":[78,144],"of":[80,90,204],"universal":[81],"retrieval,":[84],"which":[85,156,181],"evidently":[86],"increases":[87],"difficulty":[89],"effective":[91],"alignment.":[93],"In":[94,111],"this":[95,167],"paper,":[96],"propose":[98],"method":[101],"namedRelational":[102],"prOtotypicalStructure":[104],"lEarning":[105],"(ROSE)":[106],"solve":[108],"problem.":[110],"particular,":[112],"overcome":[114],"shift,":[116],"construct":[118,159],"relational":[120],"structure":[121,134,172],"depicting":[122],"cross-domain":[123],"similar":[124,140],"pairs":[125,141],"based":[126],"ranking":[128],"statistics,":[129],"then":[130],"learn":[131],"from":[132],"by":[135],"maximizing":[136],"similarity":[138],"between":[139],"compared":[142],"negatives.":[145],"Moreover,":[146],"private":[148],"are":[150],"detected":[151],"using":[152],"min-max":[154],"criterion,":[155],"helps":[157],"prototypes":[161],"Hamming":[164,179],"space.":[165],"On":[166],"basis,":[168],"combine":[170],"prototypical":[171],"learning":[173,185],"online":[175],"clustering":[176],"space,":[180],"improves":[182],"semantic":[184],"under":[186],"deficiency.":[188],"Extensive":[189],"experiments":[190],"benchmarks":[193],"demonstrate":[194],"our":[196],"ROSE":[198],"significantly":[199],"outperforms":[200],"wide":[202],"range":[203],"state-of-the-art":[205],"methods.":[206],"Our":[207],"code":[209],"available":[211],"athttps://github.com/WillDreamer/Rose.git.":[212]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}