{"id":"https://openalex.org/W3118998554","doi":"https://doi.org/10.1109/bigdata55660.2022.10020365","title":"Open Set Domain Adaptation by Extreme Value Theory","display_name":"Open Set Domain Adaptation by Extreme Value Theory","publication_year":2022,"publication_date":"2022-12-17","ids":{"openalex":"https://openalex.org/W3118998554","doi":"https://doi.org/10.1109/bigdata55660.2022.10020365","mag":"3118998554"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata55660.2022.10020365","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata55660.2022.10020365","pdf_url":null,"source":{"id":"https://openalex.org/S4363607709","display_name":"2022 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"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":"2022 IEEE International Conference on Big Data (Big Data)","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/A5101798266","display_name":"Yiming Xu","orcid":"https://orcid.org/0000-0003-3011-700X"},"institutions":[{"id":"https://openalex.org/I111979921","display_name":"Northwestern University","ror":"https://ror.org/000e0be47","country_code":"US","type":"education","lineage":["https://openalex.org/I111979921"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yiming Xu","raw_affiliation_strings":["Northwestern University,Evanston,USA","Northwestern University, Evanston, USA"],"affiliations":[{"raw_affiliation_string":"Northwestern University,Evanston,USA","institution_ids":["https://openalex.org/I111979921"]},{"raw_affiliation_string":"Northwestern University, Evanston, USA","institution_ids":["https://openalex.org/I111979921"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013049879","display_name":"Diego Klabjan","orcid":"https://orcid.org/0000-0003-4213-9281"},"institutions":[{"id":"https://openalex.org/I111979921","display_name":"Northwestern University","ror":"https://ror.org/000e0be47","country_code":"US","type":"education","lineage":["https://openalex.org/I111979921"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Diego Klabjan","raw_affiliation_strings":["Northwestern University,Evanston,USA","Northwestern University, Evanston, USA"],"affiliations":[{"raw_affiliation_string":"Northwestern University,Evanston,USA","institution_ids":["https://openalex.org/I111979921"]},{"raw_affiliation_string":"Northwestern University, Evanston, USA","institution_ids":["https://openalex.org/I111979921"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101798266"],"corresponding_institution_ids":["https://openalex.org/I111979921"],"apc_list":null,"apc_paid":null,"fwci":0.4162,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.54430857,"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":"1395","last_page":"1400"},"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/T12676","display_name":"Machine Learning and ELM","score":0.9610999822616577,"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/T10515","display_name":"Cancer-related molecular mechanisms research","score":0.9592000246047974,"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/domain-adaptation","display_name":"Domain adaptation","score":0.7603150606155396},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7226061820983887},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.5759406685829163},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5594134330749512},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.5463434457778931},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48815470933914185},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4699587821960449},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4401341378688812},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3300885558128357},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20212742686271667},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.07588165998458862}],"concepts":[{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.7603150606155396},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7226061820983887},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5759406685829163},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5594134330749512},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.5463434457778931},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48815470933914185},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4699587821960449},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4401341378688812},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3300885558128357},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20212742686271667},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.07588165998458862},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"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:10.1109/bigdata55660.2022.10020365","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata55660.2022.10020365","pdf_url":null,"source":{"id":"https://openalex.org/S4363607709","display_name":"2022 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"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":"2022 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.46000000834465027,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1686810756","https://openalex.org/W1722318740","https://openalex.org/W1934241014","https://openalex.org/W2112796928","https://openalex.org/W2149466042","https://openalex.org/W2157331557","https://openalex.org/W2163605009","https://openalex.org/W2335728318","https://openalex.org/W2526075485","https://openalex.org/W2549139847","https://openalex.org/W2557626841","https://openalex.org/W2593768305","https://openalex.org/W2766897166","https://openalex.org/W2767722847","https://openalex.org/W2770645414","https://openalex.org/W2779610669","https://openalex.org/W2787119853","https://openalex.org/W2795155917","https://openalex.org/W2798593490","https://openalex.org/W2806740420","https://openalex.org/W2897482938","https://openalex.org/W2901114541","https://openalex.org/W2914204846","https://openalex.org/W2943453641","https://openalex.org/W2948429981","https://openalex.org/W2949300070","https://openalex.org/W2949650786","https://openalex.org/W2949987290","https://openalex.org/W2950361018","https://openalex.org/W2951590222","https://openalex.org/W2952302403","https://openalex.org/W2953070460","https://openalex.org/W2953226914","https://openalex.org/W2962687275","https://openalex.org/W2963149653","https://openalex.org/W2963449071","https://openalex.org/W2963826681","https://openalex.org/W2973218493","https://openalex.org/W2979382951","https://openalex.org/W3105881229","https://openalex.org/W3173352923","https://openalex.org/W3196536640","https://openalex.org/W6639480849","https://openalex.org/W6681637710","https://openalex.org/W6695692224","https://openalex.org/W6703116779","https://openalex.org/W6746171285","https://openalex.org/W6750109254","https://openalex.org/W6762164956"],"related_works":["https://openalex.org/W4376166954","https://openalex.org/W2152148513","https://openalex.org/W4281397339","https://openalex.org/W4312910505","https://openalex.org/W3096565154","https://openalex.org/W1864954421","https://openalex.org/W2783380393","https://openalex.org/W2280198878","https://openalex.org/W2951876757","https://openalex.org/W3015298734"],"abstract_inverted_index":{"Common":[0],"domain":[1,8,12,65,76,142,154],"adaptation":[2,77,143],"techniques":[3],"assume":[4],"that":[5,82],"the":[6,10,33,37,45,47,55,63,73,80,83,86,94,98,105,114,121,124,146,150],"source":[7,64,84,115],"and":[9,85,93,109,145],"target":[11,23,87,106],"share":[13,36],"an":[14],"identical":[15],"label":[16,39,88],"space,":[17],"which":[18,135],"is":[19,43],"problematic":[20],"since":[21],"when":[22,97],"samples":[24],"are":[25,59],"unlabeled":[26],"we":[27,71],"have":[28],"no":[29],"knowledge":[30],"on":[31,140],"whether":[32],"two":[34],"domains":[35],"same":[38],"space.":[40],"When":[41],"this":[42,69],"not":[44],"case,":[46],"existing":[48],"methods":[49],"fail":[50],"to":[51,103,119],"perform":[52],"well":[53],"because":[54],"additional":[56],"unknown":[57,99,107,132],"classes":[58,100,108],"also":[60],"matched":[61],"with":[62,113,127],"during":[66],"adaptation.":[67,155],"In":[68],"paper,":[70],"tackle":[72],"open":[74],"set":[75],"problem":[78],"under":[79],"assumption":[81],"spaces":[89],"only":[90],"partially":[91],"overlap,":[92],"task":[95],"becomes":[96],"exist,":[101],"how":[102],"detect":[104],"avoid":[110],"aligning":[111],"them":[112],"domain.":[116],"We":[117],"propose":[118],"model":[120],"tail":[122],"of":[123],"entropy":[125],"distribution":[126],"Extreme":[128],"Value":[129],"Theory":[130],"for":[131],"class":[133],"detection,":[134],"has":[136],"shown":[137],"promising":[138],"performance":[139],"conventional":[141],"datasets,":[144],"proposed":[147],"method":[148],"outperforms":[149],"state-of-the-art":[151],"models":[152],"in":[153]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}