{"id":"https://openalex.org/W2563422311","doi":"https://doi.org/10.1145/3009977.3010033","title":"Unsupervised domain adaptation without source domain training samples","display_name":"Unsupervised domain adaptation without source domain training samples","publication_year":2016,"publication_date":"2016-12-18","ids":{"openalex":"https://openalex.org/W2563422311","doi":"https://doi.org/10.1145/3009977.3010033","mag":"2563422311"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1145/3009977.3010033","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5083424027","display_name":"Sudipan Saha","orcid":"https://orcid.org/0000-0002-9440-0720"},"institutions":[{"id":"https://openalex.org/I162827531","display_name":"Indian Institute of Technology Bombay","ror":"https://ror.org/02qyf5152","country_code":"IN","type":"funder","lineage":["https://openalex.org/I162827531"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sudipan Saha","raw_affiliation_strings":["Indian Institute of Technology Bombay, Mumbai, India"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology Bombay, Mumbai, India","institution_ids":["https://openalex.org/I162827531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020786167","display_name":"Biplab Banerjee","orcid":"https://orcid.org/0000-0001-8371-8138"},"institutions":[{"id":"https://openalex.org/I154851008","display_name":"Indian Institute of Technology Roorkee","ror":"https://ror.org/00582g326","country_code":"IN","type":"funder","lineage":["https://openalex.org/I154851008"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Biplab Banerjee","raw_affiliation_strings":["Indian Institute of Technology Roorkee, Roorkee, India"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology Roorkee, Roorkee, India","institution_ids":["https://openalex.org/I154851008"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079092830","display_name":"S. N. Merchant","orcid":"https://orcid.org/0000-0002-9119-6795"},"institutions":[{"id":"https://openalex.org/I162827531","display_name":"Indian Institute of Technology Bombay","ror":"https://ror.org/02qyf5152","country_code":"IN","type":"funder","lineage":["https://openalex.org/I162827531"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Shabbir N. Merchant","raw_affiliation_strings":["Indian Institute of Technology Bombay, Mumbai, India"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology Bombay, Mumbai, India","institution_ids":["https://openalex.org/I162827531"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.328,"has_fulltext":true,"fulltext_origin":"ngrams","cited_by_count":6,"citation_normalized_percentile":{"value":0.457368,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":82,"max":83},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9993,"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":0.9993,"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/T11243","display_name":"Respiratory viral infections research","score":0.9647,"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"}},{"id":"https://openalex.org/T10515","display_name":"Cancer-related molecular mechanisms research","score":0.9411,"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/discriminative-model","display_name":"Discriminative model","score":0.47835177},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain Adaptation","score":0.46358085}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7389206},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6996353},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6495317},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.63716483},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5730037},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.52150923},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.47835177},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.46358085},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4484225},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.41043985},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36520308},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1145/3009977.3010033","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life on land","score":0.55,"id":"https://metadata.un.org/sdg/15"}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":32,"referenced_works":["https://openalex.org/W1506806321","https://openalex.org/W1583837637","https://openalex.org/W158976495","https://openalex.org/W1722318740","https://openalex.org/W1941659294","https://openalex.org/W1977287321","https://openalex.org/W1978577993","https://openalex.org/W1982696459","https://openalex.org/W2004273576","https://openalex.org/W2097908878","https://openalex.org/W2100740156","https://openalex.org/W2104068492","https://openalex.org/W2111975408","https://openalex.org/W2115403315","https://openalex.org/W2128053425","https://openalex.org/W2128487019","https://openalex.org/W2132175002","https://openalex.org/W2132820034","https://openalex.org/W2158815628","https://openalex.org/W2161498107","https://openalex.org/W2162651021","https://openalex.org/W2165828254","https://openalex.org/W2168876499","https://openalex.org/W2274622268","https://openalex.org/W2296319761","https://openalex.org/W2299721312","https://openalex.org/W2612972698","https://openalex.org/W2914092092","https://openalex.org/W4232401394","https://openalex.org/W4250589301","https://openalex.org/W4285719527","https://openalex.org/W77777798"],"related_works":["https://openalex.org/W4289294429","https://openalex.org/W4287263085","https://openalex.org/W3214142563","https://openalex.org/W3186065094","https://openalex.org/W3166286441","https://openalex.org/W3136267388","https://openalex.org/W3080655457","https://openalex.org/W2949100517","https://openalex.org/W2899666933","https://openalex.org/W1487808658"],"abstract_inverted_index":{"Unsupervised":[0],"domain":[1,14,22,84,130],"adaptation":[2],"(DA)":[3],"techniques":[4],"inherently":[5],"assume":[6],"the":[7,20,34,58,63,77,98,102,119,126,134,142,146,173,181,194,209,217,223,227],"presence":[8],"of":[9,12,96,148,165,186,190,196,229],"ample":[10],"amount":[11],"source":[13,83],"training":[15],"samples":[16,99,127,176],"in":[17,56,104,118,128],"addition":[18],"to":[19,46,62,124,139],"target":[21],"test":[23],"data.":[24],"The":[25,43,109,158],"domains":[26,103],"are":[27,37],"characterized":[28],"by":[29,166],"domain-specific":[30],"probability":[31],"distributions":[32],"governing":[33],"data":[35,143,159],"which":[36,79],"substantially":[38],"different":[39,191],"from":[40,100],"each":[41,156],"other.":[42],"goal":[44],"is":[45,122,137,153,162],"build":[47],"a":[48,70,92,105,129,151,169,184,200],"task":[49],"oriented":[50],"classifier":[51,152,171],"model":[52],"that":[53,208],"performs":[54],"proportionately":[55],"both":[57,101,222],"domains.":[59],"In":[60],"contrary":[61],"standard":[64],"unsupervised":[65],"DA":[66],"setup,":[67],"we":[68,88],"propose":[69],"maximum-margin":[71],"clustering":[72,94],"(MMC)":[73],"based":[74,114,144],"framework":[75,182],"for":[76,155,172,193,204,221],"same":[78],"does":[80],"not":[81],"consider":[82],"labeled":[85],"samples.":[86],"Instead":[87],"formulate":[89],"it":[90],"as":[91],"joint":[93],"problem":[95,161],"all":[97],"common":[106],"feature":[107],"subspace.":[108],"Geodesic":[110],"Flow":[111],"Kernel":[112],"(GFK)":[113],"subspace":[115],"projection":[116],"technique":[117],"Grassmannian":[120],"manifold":[121],"adopted":[123],"cast":[125],"invariant":[131],"space.":[132],"Further,":[133],"MMC":[135],"stage":[136],"followed":[138],"simultaneously":[140],"group":[141],"on":[145,183],"maximization":[147],"margins":[149],"and":[150,199],"learned":[154],"group.":[157,178],"overlapping":[160],"taken":[163],"care":[164],"specifically":[167],"learning":[168],"SVM-KNN":[170],"potentially":[174],"unreliable":[175],"per":[177],"We":[179,206],"validate":[180],"pair":[185],"remote":[187],"sensing":[188],"images":[189],"modalities":[192],"purpose":[195],"land-cover":[197],"classification":[198],"generic":[201],"object":[202],"dataset":[203],"recognition.":[205],"observe":[207],"proposed":[210],"method":[211],"exhibits":[212],"performances":[213],"at":[214],"par":[215],"with":[216],"fully":[218],"supervised":[219],"case":[220],"tasks":[224],"but":[225],"without":[226],"requirement":[228],"costly":[230],"annotations.":[231]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2563422311","counts_by_year":[{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":3}],"updated_date":"2025-03-20T17:14:31.548669","created_date":"2017-01-06"}