{"id":"https://openalex.org/W2194668896","doi":"https://doi.org/10.1142/s0218001416510034","title":"An Efficient yet Effective Random Partitioning and Feature Weighting Approach for Transfer Learning","display_name":"An Efficient yet Effective Random Partitioning and Feature Weighting Approach for Transfer Learning","publication_year":2015,"publication_date":"2015-10-09","ids":{"openalex":"https://openalex.org/W2194668896","doi":"https://doi.org/10.1142/s0218001416510034","mag":"2194668896"},"language":"en","primary_location":{"id":"doi:10.1142/s0218001416510034","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001416510034","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-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/A5010007196","display_name":"Jafar Tahmoresnezhad","orcid":"https://orcid.org/0000-0002-4893-1272"},"institutions":[{"id":"https://openalex.org/I166459259","display_name":"Shiraz University","ror":"https://ror.org/028qtbk54","country_code":"IR","type":"education","lineage":["https://openalex.org/I166459259"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Jafar Tahmoresnezhad","raw_affiliation_strings":["Electrical and Computer Engineering School, Shiraz University, Shiraz, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering School, Shiraz University, Shiraz, Iran","institution_ids":["https://openalex.org/I166459259"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022739916","display_name":"Sattar Hashemi","orcid":"https://orcid.org/0000-0001-6981-8810"},"institutions":[{"id":"https://openalex.org/I166459259","display_name":"Shiraz University","ror":"https://ror.org/028qtbk54","country_code":"IR","type":"education","lineage":["https://openalex.org/I166459259"]}],"countries":["IR"],"is_corresponding":true,"raw_author_name":"Sattar Hashemi","raw_affiliation_strings":["Electrical and Computer Engineering School, Shiraz University, Shiraz, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering School, Shiraz University, Shiraz, Iran","institution_ids":["https://openalex.org/I166459259"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5022739916"],"corresponding_institution_ids":["https://openalex.org/I166459259"],"apc_list":null,"apc_paid":null,"fwci":1.3355,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.86590031,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"30","issue":"02","first_page":"1651003","last_page":"1651003"},"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":0.9998999834060669,"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":0.9998999834060669,"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":0.9767000079154968,"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":0.9132000207901001,"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/computer-science","display_name":"Computer science","score":0.6865668892860413},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.6651557087898254},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6613404154777527},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6564610600471497},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.6184697151184082},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5575321912765503},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5299416780471802},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5184866786003113},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5148062109947205},{"id":"https://openalex.org/keywords/disjoint-sets","display_name":"Disjoint sets","score":0.5146204233169556},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.48472070693969727},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.47926685214042664},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4544631838798523},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.4382787048816681},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4351278245449066},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.4337380826473236},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.27306637167930603},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21785303950309753}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6865668892860413},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.6651557087898254},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6613404154777527},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6564610600471497},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.6184697151184082},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5575321912765503},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5299416780471802},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5184866786003113},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5148062109947205},{"id":"https://openalex.org/C45340560","wikidata":"https://www.wikidata.org/wiki/Q215382","display_name":"Disjoint sets","level":2,"score":0.5146204233169556},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.48472070693969727},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.47926685214042664},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4544631838798523},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.4382787048816681},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4351278245449066},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.4337380826473236},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.27306637167930603},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21785303950309753},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"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/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0218001416510034","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001416510034","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6399999856948853,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W143806433","https://openalex.org/W1986614398","https://openalex.org/W1997399503","https://openalex.org/W2004273576","https://openalex.org/W2005650084","https://openalex.org/W2034741743","https://openalex.org/W2085269372","https://openalex.org/W2087977130","https://openalex.org/W2100664256","https://openalex.org/W2115403315","https://openalex.org/W2120708938","https://openalex.org/W2159570078","https://openalex.org/W2164943005","https://openalex.org/W2165698076","https://openalex.org/W2596585349"],"related_works":["https://openalex.org/W4256429076","https://openalex.org/W1971174658","https://openalex.org/W2099195351","https://openalex.org/W2012063272","https://openalex.org/W2348092930","https://openalex.org/W2138685729","https://openalex.org/W2062850566","https://openalex.org/W2440023763","https://openalex.org/W2962474440","https://openalex.org/W2791025012"],"abstract_inverted_index":{"One":[0],"of":[1,72,87,173,195],"the":[2,79,84,108,138,153,166,171],"serious":[3,64],"challenges":[4,65],"in":[5,66,82,143,152],"machine":[6],"learning":[7,96,121,230],"and":[8,35,53,74,97,122,169,176,207,219],"pattern":[9],"recognition":[10],"is":[11,32,111,150],"to":[12,20,38,100,127,161,188,191],"transfer":[13,39,95,120,229],"knowledge":[14,40],"from":[15,41,58],"related":[16],"but":[17],"different":[18,59],"domains":[19,142],"a":[21,33,118,200,205],"new":[22],"unlabeled":[23],"domain.":[24],"Feature":[25],"selection":[26],"with":[27,69,102,199],"maximum":[28],"mean":[29],"discrepancy":[30],"(f-MMD)":[31],"novel":[34,119,201],"effective":[36,208],"approach":[37],"source":[42,177],"domain":[43,48,103,167,178],"(training":[44],"set)":[45,50],"into":[46],"target":[47],"(test":[49],"where":[51,147],"training":[52],"test":[54,154],"sets":[55,197],"are":[56],"drawn":[57],"distributions.":[60],"However,":[61],"f-MMD":[62,77],"has":[63],"facing":[67],"datasets":[68,221],"large":[70],"number":[71],"samples":[73],"features.":[75],"Moreover,":[76,156],"ignores":[78],"feature-label":[80,159],"relation":[81,160,172],"finding":[83],"reduced":[85,209],"representation":[86,210],"dataset.":[88],"In":[89,180],"this":[90,181],"paper,":[91],"we":[92,183],"exploit":[93],"jointly":[94],"class":[98,123],"discrimination":[99,124],"cope":[101],"shift":[104],"problem":[105,203],"on":[106,217],"which":[107],"distribution":[109,139],"difference":[110,140],"considerably":[112],"large.":[113],"We":[114],"therefore":[115],"put":[116],"forward":[117],"approach,":[125],"referred":[126],"as":[128],"RandOm":[129],"k-samplesets":[130],"feature":[131],"Weighting":[132],"Approach":[133],"(ROWA).":[134],"Specifically,":[135],"ROWA":[136,157,224],"reduces":[137],"across":[141,213],"an":[144],"unsupervised":[145],"manner":[146],"no":[148],"label":[149],"available":[151],"set.":[155],"exploits":[158],"separate":[162],"various":[163],"classes":[164],"alongside":[165],"transfer,":[168],"augments":[170],"selected":[174],"features":[175],"labels.":[179],"work,":[182],"employ":[184],"disjoint/overlapping":[185],"small-sized":[186],"samplesets":[187],"iteratively":[189],"converge":[190],"final":[192],"solution.":[193],"Employment":[194],"local":[196],"along":[198],"optimization":[202],"constructs":[204],"robust":[206],"for":[211],"adaptation":[212],"domains.":[214],"Extensive":[215],"experiments":[216],"real":[218],"synthetic":[220],"verify":[222],"that":[223],"can":[225],"significantly":[226],"outperform":[227],"state-of-the-art":[228],"approaches.":[231]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":3}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}