{"id":"https://openalex.org/W3094416266","doi":"https://doi.org/10.1145/3340531.3412083","title":"Robust Normalized Squares Maximization for Unsupervised Domain Adaptation","display_name":"Robust Normalized Squares Maximization for Unsupervised Domain Adaptation","publication_year":2020,"publication_date":"2020-10-19","ids":{"openalex":"https://openalex.org/W3094416266","doi":"https://doi.org/10.1145/3340531.3412083","mag":"3094416266"},"language":"en","primary_location":{"id":"doi:10.1145/3340531.3412083","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3340531.3412083","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM International Conference on Information &amp; Knowledge Management","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/A5101890698","display_name":"Wenju Zhang","orcid":"https://orcid.org/0000-0003-1749-0838"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wenju Zhang","raw_affiliation_strings":["National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100368865","display_name":"Xiang Zhang","orcid":"https://orcid.org/0000-0002-5201-3802"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiang Zhang","raw_affiliation_strings":["National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069241620","display_name":"Qing Liao","orcid":"https://orcid.org/0000-0003-1012-5301"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qing Liao","raw_affiliation_strings":["Harbin Institute of Technology, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology, Shenzhen, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016603628","display_name":"Wenjing Yang","orcid":"https://orcid.org/0000-0002-6997-0406"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenjing Yang","raw_affiliation_strings":["National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060251766","display_name":"Long Lan","orcid":"https://orcid.org/0000-0002-4238-8985"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Long Lan","raw_affiliation_strings":["National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061811574","display_name":"Zhigang Luo","orcid":"https://orcid.org/0000-0002-7552-201X"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhigang Luo","raw_affiliation_strings":["National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5101890698"],"corresponding_institution_ids":["https://openalex.org/I170215575"],"apc_list":null,"apc_paid":null,"fwci":0.5302,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.73339793,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"2317","last_page":"2320"},"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":0.9998000264167786,"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":0.9998000264167786,"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":0.9686999917030334,"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/normalization","display_name":"Normalization (sociology)","score":0.6974716782569885},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6801649332046509},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.6532515287399292},{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.5733935832977295},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5106826424598694},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.493627667427063},{"id":"https://openalex.org/keywords/norm","display_name":"Norm (philosophy)","score":0.4450070559978485},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.44427207112312317},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.438912034034729},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43832024931907654},{"id":"https://openalex.org/keywords/least-squares-function-approximation","display_name":"Least-squares function approximation","score":0.43474531173706055},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40728598833084106},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.2883029282093048},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2574247121810913},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.14913281798362732},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.09177941083908081}],"concepts":[{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.6974716782569885},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6801649332046509},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.6532515287399292},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.5733935832977295},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5106826424598694},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.493627667427063},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.4450070559978485},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.44427207112312317},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.438912034034729},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43832024931907654},{"id":"https://openalex.org/C9936470","wikidata":"https://www.wikidata.org/wiki/Q6510405","display_name":"Least-squares function approximation","level":3,"score":0.43474531173706055},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40728598833084106},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.2883029282093048},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2574247121810913},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.14913281798362732},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.09177941083908081},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3340531.3412083","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3340531.3412083","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM International Conference on Information &amp; Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7200000286102295,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1722318740","https://openalex.org/W2053090063","https://openalex.org/W2171837816","https://openalex.org/W2194775991","https://openalex.org/W2293363371","https://openalex.org/W2627183927","https://openalex.org/W2795155917","https://openalex.org/W2951670162","https://openalex.org/W2964278684","https://openalex.org/W2979920800","https://openalex.org/W2981512393","https://openalex.org/W2982204955","https://openalex.org/W3035576098"],"related_works":["https://openalex.org/W2016839265","https://openalex.org/W1991269640","https://openalex.org/W2018445155","https://openalex.org/W4283069728","https://openalex.org/W2946038180","https://openalex.org/W2508457823","https://openalex.org/W1863050261","https://openalex.org/W2058991683","https://openalex.org/W2626335822","https://openalex.org/W3094416266"],"abstract_inverted_index":{"Unsupervised":[0],"domain":[1,11,17],"adaptation":[2],"(UDA)":[3],"attempts":[4],"to":[5,15,27,43,81,84,96,129,159],"transfer":[6],"specific":[7],"knowledge":[8],"from":[9],"one":[10],"with":[12,101,127],"labeled":[13],"data":[14],"another":[16],"without":[18],"labels.":[19],"Recently,":[20],"maximum":[21,60],"squares":[22,53,61,68],"loss":[23,56,126],"has":[24,40],"been":[25],"proposed":[26],"tackle":[28],"UDA":[29],"problem":[30],"but":[31],"it":[32],"does":[33],"not":[34],"consider":[35],"the":[36,59,65,76,87,93,124,131,147],"prediction":[37],"diversity":[38],"which":[39,58],"proven":[41],"beneficial":[42],"UDA.":[44],"In":[45],"this":[46],"paper,":[47],"we":[48],"propose":[49,115],"a":[50,116],"novel":[51],"normalized":[52,63],"maximization":[54],"(NSM)":[55],"in":[57],"is":[62,98,164],"by":[64,122],"sum":[66],"of":[67,69,79,119,133,138,149],"class":[70,77,103],"sizes.":[71],"The":[72,162],"normalization":[73],"term":[74],"enforces":[75],"sizes":[78],"predictions":[80],"be":[82],"balanced":[83,102],"explicitly":[85],"increase":[86],"diversity.":[88],"Theoretical":[89],"analysis":[90],"shows":[91],"that":[92],"optimal":[94],"solution":[95],"NSM":[97,106,151],"one-hot":[99],"vectors":[100],"sizes,":[104],"i.e.,":[105],"encourages":[107],"both":[108,150],"discriminate":[109],"and":[110,135,152],"diverse":[111],"predictions.":[112],"We":[113],"further":[114],"robust":[117],"variant":[118],"NSM,":[120],"RNSM,":[121],"replacing":[123],"square":[125],"L2,1-norm":[128],"reduce":[130],"influence":[132],"outliers":[134],"noises.":[136],"Experiments":[137],"cross-domain":[139],"image":[140],"classification":[141],"on":[142],"two":[143],"benchmark":[144],"datasets":[145],"illustrate":[146],"effectiveness":[148],"RNSM.":[153],"RNSM":[154],"achieves":[155],"promising":[156],"performance":[157],"compared":[158],"state-of-the-art":[160],"methods.":[161],"code":[163],"available":[165],"at":[166],"https://github.com/wj-zhang/NSM.":[167]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
