{"id":"https://openalex.org/W2963815055","doi":"https://doi.org/10.24963/ijcai.2017/272","title":"Theoretic Analysis and Extremely Easy Algorithms for Domain Adaptive Feature Learning","display_name":"Theoretic Analysis and Extremely Easy Algorithms for Domain Adaptive Feature Learning","publication_year":2017,"publication_date":"2017-07-28","ids":{"openalex":"https://openalex.org/W2963815055","doi":"https://doi.org/10.24963/ijcai.2017/272","mag":"2963815055"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2017/272","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2017/272","pdf_url":"https://www.ijcai.org/proceedings/2017/0272.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2017/0272.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5024453719","display_name":"Wenhao Jiang","orcid":"https://orcid.org/0000-0002-0795-366X"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wenhao Jiang","raw_affiliation_strings":["Tencent AI Lab","Tencent AI Lab, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent AI Lab","institution_ids":["https://openalex.org/I2250653659"]},{"raw_affiliation_string":"Tencent AI Lab, P. R. China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015874725","display_name":"Cheng Deng","orcid":"https://orcid.org/0000-0003-2620-3247"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cheng Deng","raw_affiliation_strings":["School of Electronic Engineering, Xidian University, Shaanxi, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, Xidian University, Shaanxi, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100431792","display_name":"Wei Liu","orcid":"https://orcid.org/0000-0002-3865-8145"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Liu","raw_affiliation_strings":["Tencent AI Lab","Tencent AI Lab, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent AI Lab","institution_ids":["https://openalex.org/I2250653659"]},{"raw_affiliation_string":"Tencent AI Lab, P. R. China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003222421","display_name":"Feiping Nie","orcid":"https://orcid.org/0000-0002-0871-6519"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feiping Nie","raw_affiliation_strings":["Northwestern Polytechnical University, Xi\u2019an, 710072, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northwestern Polytechnical University, Xi\u2019an, 710072, P. R. China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043016512","display_name":"Fu-Lai Chung","orcid":"https://orcid.org/0000-0001-5294-8168"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Fu-lai Chung","raw_affiliation_strings":["Hong Kong Polytechnic University","Hong Kong Polytechnic University, Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hong Kong Polytechnic University","institution_ids":["https://openalex.org/I14243506"]},{"raw_affiliation_string":"Hong Kong Polytechnic University, Hong Kong","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060016795","display_name":"Heng Huang","orcid":"https://orcid.org/0000-0002-3483-8333"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]},{"id":"https://openalex.org/I189196454","display_name":"The University of Texas at Arlington","ror":"https://ror.org/019kgqr73","country_code":"US","type":"education","lineage":["https://openalex.org/I189196454"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Heng Huang","raw_affiliation_strings":["University of Texas at Arlington, USA","Xidian University, Xi'an 710071, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Texas at Arlington, USA","institution_ids":["https://openalex.org/I189196454"]},{"raw_affiliation_string":"Xidian University, Xi'an 710071, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5024453719"],"corresponding_institution_ids":["https://openalex.org/I2250653659"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1958","last_page":"1964"},"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":0.9933000206947327,"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":0.9933000206947327,"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/T10028","display_name":"Topic Modeling","score":0.9702000021934509,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9448999762535095,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.824583888053894},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.7072558403015137},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.7045422196388245},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.6312178373336792},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6192803978919983},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6089363694190979},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.5972377061843872},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5365377068519592},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.4942364990711212},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4145072102546692},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3919838070869446},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3829501271247864},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0919012725353241}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.824583888053894},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.7072558403015137},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.7045422196388245},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.6312178373336792},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6192803978919983},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6089363694190979},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.5972377061843872},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5365377068519592},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.4942364990711212},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4145072102546692},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3919838070869446},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3829501271247864},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0919012725353241},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"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/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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.24963/ijcai.2017/272","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2017/272","pdf_url":"https://www.ijcai.org/proceedings/2017/0272.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},{"id":"pmh:oai:ira.lib.polyu.edu.hk:10397/105691","is_oa":true,"landing_page_url":"http://hdl.handle.net/10397/105691","pdf_url":"http://ira.lib.polyu.edu.hk/bitstream/10397/105691/1/0272.pdf","source":{"id":"https://openalex.org/S4306400205","display_name":"PolyU Institutional Research Archive (Hong Kong Polytechnic University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I14243506","host_organization_name":"Hong Kong Polytechnic University","host_organization_lineage":["https://openalex.org/I14243506"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference Paper"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2017/272","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2017/272","pdf_url":"https://www.ijcai.org/proceedings/2017/0272.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1989426510","display_name":"ABI Innovation: A New Automated Data Integration, Annotations, and Interaction Network Inference System for Analyzing Drosophila Gene Expression","funder_award_id":"1356628","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G2464782121","display_name":"III: Medium: Collaborative Research: Robust Large-Scale Electronic Medical Record Data Mining Framework to Conduct Risk Stratification for Personalized Intervention","funder_award_id":"1302675","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3559141165","display_name":null,"funder_award_id":"DBI 1356628","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7136375676","display_name":null,"funder_award_id":"IIS 1344152","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7702841122","display_name":"SCH: EXP: Collaborative Research: Privacy-Preserving Framework for Publishing Electronic Healthcare Records","funder_award_id":"1344152","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G942013628","display_name":null,"funder_award_id":"IIS 1302675","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320322598","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2963815055.pdf","grobid_xml":"https://content.openalex.org/works/W2963815055.grobid-xml"},"referenced_works_count":26,"referenced_works":["https://openalex.org/W22861983","https://openalex.org/W1488435683","https://openalex.org/W1544165511","https://openalex.org/W1577269164","https://openalex.org/W2026731079","https://openalex.org/W2032536435","https://openalex.org/W2034368206","https://openalex.org/W2043228833","https://openalex.org/W2095723734","https://openalex.org/W2096873754","https://openalex.org/W2105523772","https://openalex.org/W2110091014","https://openalex.org/W2112483442","https://openalex.org/W2115124945","https://openalex.org/W2118045473","https://openalex.org/W2120149881","https://openalex.org/W2131953535","https://openalex.org/W2139122730","https://openalex.org/W2141067830","https://openalex.org/W2149466042","https://openalex.org/W2156557681","https://openalex.org/W2158108973","https://openalex.org/W2163302275","https://openalex.org/W2215421138","https://openalex.org/W2886141085","https://openalex.org/W2963275094"],"related_works":["https://openalex.org/W4394775207","https://openalex.org/W4389474468","https://openalex.org/W4300172004","https://openalex.org/W4321649381","https://openalex.org/W2997645659","https://openalex.org/W3180787869","https://openalex.org/W3203792196","https://openalex.org/W2955455867","https://openalex.org/W4295929828","https://openalex.org/W2400428875"],"abstract_inverted_index":{"Domain":[0],"adaptation":[1,83,114,144],"problems":[2,40],"arise":[3],"in":[4,32,42,66,78,140],"a":[5,10,18,105],"variety":[6],"of":[7,61,88,136,142],"applications,":[8],"where":[9],"training":[11],"dataset":[12,20],"from":[13,21,152],"the":[14,22,46,49,85,89,134,137,153],"source":[15,50,90],"domain":[16,24,72,91,95,113,143],"and":[17,51,93,149],"test":[19],"target":[23,52,94],"typically":[25],"follow":[26],"different":[27],"distributions.":[28,53],"The":[29],"primary":[30],"difficulty":[31],"designing":[33],"effective":[34],"learning":[35,63,110,130],"models":[36],"to":[37,44,80,127],"solve":[38],"such":[39],"lies":[41],"how":[43],"bridge":[45],"gap":[47],"between":[48],"In":[54],"this":[55],"paper,":[56],"we":[57],"provide":[58],"comprehensive":[59],"analysis":[60,75],"feature":[62,109,129],"algorithms":[64,139],"used":[65],"conjunction":[67],"with":[68],"linear":[69],"classifiers":[70],"for":[71,112],"adaptation.":[73],"Our":[74],"shows":[76],"that":[77],"order":[79],"achieve":[81],"good":[82],"performance,":[84],"second":[86],"moments":[87],"distribution":[92,96],"should":[97],"be":[98],"similar.":[99],"Based":[100],"on":[101,146],"our":[102,118],"new":[103],"analysis,":[104],"novel":[106],"extremely":[107],"easy":[108],"algorithm":[111,119],"is":[115,120],"proposed.":[116],"Furthermore,":[117],"extended":[121],"by":[122],"leveraging":[123],"multiple":[124],"layers,":[125],"leading":[126],"another":[128],"algorithm.":[131],"We":[132],"evaluate":[133],"effectiveness":[135],"proposed":[138],"terms":[141],"tasks":[145],"Amazon":[147],"review":[148],"spam":[150],"datasets":[151],"ECML/PKDD":[154],"2006":[155],"discovery":[156],"challenge.":[157]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}