{"id":"https://openalex.org/W2331501241","doi":"https://doi.org/10.5244/c.29.96","title":"Bridging the Domain Shift by Domain Adaptive Dictionary Learning","display_name":"Bridging the Domain Shift by Domain Adaptive Dictionary Learning","publication_year":2015,"publication_date":"2015-01-01","ids":{"openalex":"https://openalex.org/W2331501241","doi":"https://doi.org/10.5244/c.29.96","mag":"2331501241"},"language":"en","primary_location":{"id":"doi:10.5244/c.29.96","doi":"https://doi.org/10.5244/c.29.96","is_oa":false,"landing_page_url":"https://doi.org/10.5244/c.29.96","pdf_url":null,"source":{"id":"https://openalex.org/S7407088578","display_name":"British Machine Vision Conference (BMVC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"Procedings of the British Machine Vision Conference 2015","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5102918211","display_name":"Hongyu Xu","orcid":"https://orcid.org/0000-0002-9075-2307","observed_orcids":["https://orcid.org/0000-0002-9075-2307","https://orcid.org/0009-0007-4071-3047"]},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hongyu Xu","raw_affiliation_strings":["University of Maryland - College Park"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Maryland - College Park","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072742668","display_name":"Jingjing Zheng","orcid":"https://orcid.org/0000-0003-1955-5308","observed_orcids":["https://orcid.org/0000-0003-1955-5308"]},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jingjing Zheng","raw_affiliation_strings":["University of Maryland - College Park"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Maryland - College Park","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102762707","display_name":"Rama Chellappa","orcid":"https://orcid.org/0000-0002-7638-1650","observed_orcids":["https://orcid.org/0000-0002-7638-1650"]},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rama Chellappa","raw_affiliation_strings":["University of Maryland - College Park"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Maryland - College Park","institution_ids":["https://openalex.org/I66946132"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I66946132"],"apc_list":null,"apc_paid":null,"fwci":1.8154,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.88602195,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"96.1","last_page":"96.12"},"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":0.9980000257492065,"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":0.9980000257492065,"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":0.00039999998989515007,"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/T10057","display_name":"Face and Expression Recognition","score":0.00019999999494757503,"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/domain-adaptation","display_name":"domain adaptation","score":0.9449999928474426},{"id":"https://openalex.org/keywords/unsupervised-domain-adaptation","display_name":"unsupervised domain adaptation","score":0.9259999990463257},{"id":"https://openalex.org/keywords/dictionary-learning","display_name":"dictionary learning","score":0.9860000014305115},{"id":"https://openalex.org/keywords/sparse-coding","display_name":"sparse coding","score":0.824999988079071},{"id":"https://openalex.org/keywords/intermediate-domain","display_name":"intermediate domain","score":0.8999999761581421},{"id":"https://openalex.org/keywords/specialized-dictionaries","display_name":"specialized dictionaries","score":0.9210000038146973},{"id":"https://openalex.org/keywords/sparse-representation","display_name":"sparse representation","score":0.42500001192092896}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7654043436050415},{"id":"https://openalex.org/C2988886741","wikidata":"https://www.wikidata.org/wiki/Q25304494","display_name":"Dictionary learning","level":3,"score":0.7064679861068726},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6348254680633545},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.6321879029273987},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5262362360954285},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5216303467750549},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.501643180847168},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4993913173675537},{"id":"https://openalex.org/C154771677","wikidata":"https://www.wikidata.org/wiki/Q17098361","display_name":"K-SVD","level":3,"score":0.41130900382995605},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.41054025292396545},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3641093671321869},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.2882516384124756},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12406495213508606},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.095052570104599},{"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"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":[{"id":"doi:10.5244/c.29.96","doi":"https://doi.org/10.5244/c.29.96","is_oa":false,"landing_page_url":"https://doi.org/10.5244/c.29.96","pdf_url":null,"source":{"id":"https://openalex.org/S7407088578","display_name":"British Machine Vision Conference (BMVC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"Procedings of the British Machine Vision Conference 2015","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W304676660","https://openalex.org/W1682040381","https://openalex.org/W1722318740","https://openalex.org/W1784617778","https://openalex.org/W1852255964","https://openalex.org/W1978920452","https://openalex.org/W1985967702","https://openalex.org/W1988348003","https://openalex.org/W2006793117","https://openalex.org/W2033547469","https://openalex.org/W2057266281","https://openalex.org/W2064447488","https://openalex.org/W2090923791","https://openalex.org/W2092227224","https://openalex.org/W2096943734","https://openalex.org/W2099501835","https://openalex.org/W2104068492","https://openalex.org/W2107250100","https://openalex.org/W2119605622","https://openalex.org/W2120354757","https://openalex.org/W2128053425","https://openalex.org/W2129306288","https://openalex.org/W2132175002","https://openalex.org/W2137695006","https://openalex.org/W2149466042","https://openalex.org/W2158815628","https://openalex.org/W2160039895","https://openalex.org/W2160547390","https://openalex.org/W2167260591","https://openalex.org/W2171370495","https://openalex.org/W2996852294"],"related_works":["https://openalex.org/W7098630658","https://openalex.org/W2330762779","https://openalex.org/W2508027360","https://openalex.org/W2295132147","https://openalex.org/W592818541","https://openalex.org/W2949308483","https://openalex.org/W4323543294","https://openalex.org/W2132175002","https://openalex.org/W1985967702","https://openalex.org/W2797628751"],"abstract_inverted_index":{"Domain":[0],"adaptation":[1],"(DA)":[2],"tackles":[3],"the":[4,9,45,52,55,74,108,143,148,164,169,182,188,197,205,209,231,239,244,251,260,277,289,296,301,314,356,360,366,374,379,384,388,394],"problem":[5,50],"where":[6,51,286,363],"data":[7,175,219,284,312,402],"from":[8],"training":[10,25],"set":[11,16,102,372],"(source":[12],"domain)":[13,18],"and":[14,26,36,112,125,155,159,256,282,293,310,324,339,400],"test":[15],"(target":[17],"have":[19,181],"different":[20,33],"underlying":[21],"distributions.":[22],"For":[23],"instance,":[24],"testing":[27],"images":[28,77],"may":[29],"be":[30,81,276,377],"acquired":[31],"under":[32],"environments,":[34],"viewpoints":[35],"illumination":[37],"conditions.":[38],"In":[39],"this":[40,223],"paper,":[41],"we":[42,91,145,167,201,248,349,386],"focus":[43],"on":[44],"more":[46],"challenging":[47],"unsupervised":[48],"DA":[49],"samples":[53,299],"in":[54,84,134,176,204,222,242,300,313],"target":[56,113,160,174,198,218,245,283,311,401],"domain":[57,207,317],"are":[58,295,318,342],"unlabeled.":[59],"It":[60],"is":[61,263,288,333,365],"noticed":[62],"that":[63,76],"dictionary":[64,88,96,124,150,192,234,257,332,358,390],"learning":[65,97,131],"has":[66],"gained":[67],"a":[68,93,101,122,126],"lot":[69],"of":[70,78,103,120,138,173,217,253,280,298,307,368,378,397],"popularity":[71],"due":[72],"to":[73,99,180,194,213,229,354,376],"fact":[75],"interest":[79],"could":[80],"reconstructed":[82],"sparsely":[83],"an":[85],"appropriately":[86],"learned":[87],"[1].":[89],"Specifically,":[90],"propose":[92],"novel":[94],"domain-adaptive":[95],"approach":[98,116],"generate":[100],"intermediate":[104,316,369],"domains":[105,179],"which":[106],"bridge":[107],"gap":[109],"between":[110,250],"source":[111,158,281,309,399],"domains.":[114,161,303,370],"Our":[115],"defines":[117],"two":[118,302],"types":[119],"dictionaries:":[121],"common":[123,149,331,389],"domain-specific":[127,233,357],"dictionary.":[128],"The":[129,304,330],"overall":[130],"process":[132],"illustrated":[133],"Figure":[135],"1":[136],"consists":[137],"three":[139],"steps:":[140],"(1)":[141],"At":[142,163,383],"beginning,":[144,385],"first":[146],"learn":[147,387],"DC,":[151,336],"domainspecific":[152],"dictionaries":[153,203,341,375],"D0":[154],"Dt":[156,346],"for":[157,359],"(2)":[162],"k-th":[165,206,315,361],"step,":[166],"enforce":[168],"recovered":[170,308],"feature":[171,215,278,290,305],"representations":[172,216,279,306],"all":[177,373],"available":[178],"same":[183,380],"sparse":[184,211,254],"codes,":[185],"while":[186],"adapting":[187],"most":[189],"recently":[190],"obtained":[191],"Dk":[193,228],"better":[195],"represent":[196],"domain.":[199,224],"Then":[200,247],"multiply":[202],"with":[208],"corresponding":[210],"codes":[212],"recover":[214],"Xk":[220,325],"t":[221,273,326],"(3)":[225],"We":[226,371],"update":[227],"find":[230],"next":[232],"Dk+1":[235],"by":[236,392],"further":[237],"minimizing":[238,393],"reconstruction":[240,395],"error":[241,396],"representing":[243],"data.":[246],"alternate":[249],"steps":[252],"coding":[255],"updating":[258],"until":[259],"stopping":[261],"criteria":[262],"satisfied.":[264],"Notations:":[265],"Let":[266],"X":[267,272],"s":[268],"\u2208":[269,274,322,327],"Rd\u00d7Ns":[270,323],",":[271],"Rd\u00d7Nt":[275,328],"respectively,":[285],"d":[287],"dimension,":[291],"Ns":[292],"Nt":[294],"number":[297,367],"denoted":[319,334,343],"as":[320,335,344,403],"Xs":[321],"respectively.":[329,347],"whereas":[337],"source-specific":[338],"targetspecific":[340],"D0,":[345],"Similarly,":[348],"use":[350],"Dk,k":[351],"=":[352],"1...N":[353],"denote":[355],"domain,":[362],"N":[364],"size":[381],"\u2208Rd\u00d7n.":[382],"DC":[391],"both":[398],"follows:":[404]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":1}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2016-06-24T00:00:00"}