{"id":"https://openalex.org/W4307093714","doi":"https://doi.org/10.1109/tnnls.2022.3212924","title":"A Co-Training Framework for Heterogeneous Heuristic Domain Adaptation","display_name":"A Co-Training Framework for Heterogeneous Heuristic Domain Adaptation","publication_year":2022,"publication_date":"2022-11-03","ids":{"openalex":"https://openalex.org/W4307093714","doi":"https://doi.org/10.1109/tnnls.2022.3212924","pmid":"https://pubmed.ncbi.nlm.nih.gov/36269922"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2022.3212924","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3212924","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5057021534","display_name":"Cuie Yang","orcid":"https://orcid.org/0000-0003-1997-1854"},"institutions":[{"id":"https://openalex.org/I41156924","display_name":"Victoria University of Wellington","ror":"https://ror.org/0040r6f76","country_code":"NZ","type":"education","lineage":["https://openalex.org/I41156924"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Cuie Yang","raw_affiliation_strings":["School of Engineering and Computer Science, Victoria University of Wellington, Wellington, New Zealand"],"raw_orcid":"https://orcid.org/0000-0003-1997-1854","affiliations":[{"raw_affiliation_string":"School of Engineering and Computer Science, Victoria University of Wellington, Wellington, New Zealand","institution_ids":["https://openalex.org/I41156924"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077569089","display_name":"Bing Xue","orcid":"https://orcid.org/0000-0002-4865-8026"},"institutions":[{"id":"https://openalex.org/I41156924","display_name":"Victoria University of Wellington","ror":"https://ror.org/0040r6f76","country_code":"NZ","type":"education","lineage":["https://openalex.org/I41156924"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Bing Xue","raw_affiliation_strings":["School of Engineering and Computer Science, Victoria University of Wellington, Wellington, New Zealand"],"raw_orcid":"https://orcid.org/0000-0002-4865-8026","affiliations":[{"raw_affiliation_string":"School of Engineering and Computer Science, Victoria University of Wellington, Wellington, New Zealand","institution_ids":["https://openalex.org/I41156924"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025285243","display_name":"Kay Chen Tan","orcid":"https://orcid.org/0000-0002-6802-2463"},"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":"Kay Chen Tan","raw_affiliation_strings":["Department of Computing, The Hong Kong Polytechnic University, Hung Hom, Hong Kong SAR"],"raw_orcid":"https://orcid.org/0000-0002-6802-2463","affiliations":[{"raw_affiliation_string":"Department of Computing, The Hong Kong Polytechnic University, Hung Hom, Hong Kong SAR","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100400258","display_name":"Mengjie Zhang","orcid":"https://orcid.org/0000-0003-4463-9538"},"institutions":[{"id":"https://openalex.org/I41156924","display_name":"Victoria University of Wellington","ror":"https://ror.org/0040r6f76","country_code":"NZ","type":"education","lineage":["https://openalex.org/I41156924"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Mengjie Zhang","raw_affiliation_strings":["School of Engineering and Computer Science, Victoria University of Wellington, Wellington, New Zealand"],"raw_orcid":"https://orcid.org/0000-0003-4463-9538","affiliations":[{"raw_affiliation_string":"School of Engineering and Computer Science, Victoria University of Wellington, Wellington, New Zealand","institution_ids":["https://openalex.org/I41156924"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2645,"currency":"USD","value_usd":2645},"apc_paid":null,"fwci":0.8704,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.78201442,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"35","issue":"5","first_page":"6863","last_page":"6877"},"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":0.9532999992370605,"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":0.9532999992370605,"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/classifier","display_name":"Classifier (UML)","score":0.801399827003479},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7725695371627808},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.7120102643966675},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7026400566101074},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.6613197326660156},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5217003226280212},{"id":"https://openalex.org/keywords/subnetwork","display_name":"Subnetwork","score":0.4871072769165039},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4775967597961426},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.4276014268398285},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4159785807132721},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.414512038230896},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.41389814019203186},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11564919352531433}],"concepts":[{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.801399827003479},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7725695371627808},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.7120102643966675},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7026400566101074},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.6613197326660156},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5217003226280212},{"id":"https://openalex.org/C2780186347","wikidata":"https://www.wikidata.org/wiki/Q11414","display_name":"Subnetwork","level":2,"score":0.4871072769165039},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4775967597961426},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.4276014268398285},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4159785807132721},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.414512038230896},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.41389814019203186},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11564919352531433},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2022.3212924","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3212924","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:36269922","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36269922","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":"Journal Article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.6800000071525574}],"awards":[{"id":"https://openalex.org/G7942516388","display_name":null,"funder_award_id":"61876169","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":60,"referenced_works":["https://openalex.org/W8870360","https://openalex.org/W1722318740","https://openalex.org/W2048679005","https://openalex.org/W2096943734","https://openalex.org/W2115403315","https://openalex.org/W2163605009","https://openalex.org/W2165698076","https://openalex.org/W2187089797","https://openalex.org/W2194775991","https://openalex.org/W2486431868","https://openalex.org/W2519898457","https://openalex.org/W2541678333","https://openalex.org/W2593768305","https://openalex.org/W2605488490","https://openalex.org/W2627183927","https://openalex.org/W2766897166","https://openalex.org/W2770645414","https://openalex.org/W2798328860","https://openalex.org/W2798681837","https://openalex.org/W2948959975","https://openalex.org/W2962835731","https://openalex.org/W2963168418","https://openalex.org/W2963214104","https://openalex.org/W2963532621","https://openalex.org/W2963693396","https://openalex.org/W2963789515","https://openalex.org/W2964288524","https://openalex.org/W2991405316","https://openalex.org/W2995504922","https://openalex.org/W2998115938","https://openalex.org/W2998351473","https://openalex.org/W2999216888","https://openalex.org/W3000097396","https://openalex.org/W3010448819","https://openalex.org/W3034591020","https://openalex.org/W3039883906","https://openalex.org/W3040617750","https://openalex.org/W3106895564","https://openalex.org/W3110059533","https://openalex.org/W3135384301","https://openalex.org/W3138953622","https://openalex.org/W3176602994","https://openalex.org/W3199097846","https://openalex.org/W4245888765","https://openalex.org/W4300988298","https://openalex.org/W6600367688","https://openalex.org/W6677741084","https://openalex.org/W6682132143","https://openalex.org/W6683633756","https://openalex.org/W6684191040","https://openalex.org/W6687400500","https://openalex.org/W6688152027","https://openalex.org/W6695692224","https://openalex.org/W6713955831","https://openalex.org/W6725448924","https://openalex.org/W6735050833","https://openalex.org/W6746171285","https://openalex.org/W6750109254","https://openalex.org/W6761687776","https://openalex.org/W6763066025"],"related_works":["https://openalex.org/W3080655457","https://openalex.org/W4385571636","https://openalex.org/W2145868540","https://openalex.org/W3166286441","https://openalex.org/W3214142563","https://openalex.org/W3136267388","https://openalex.org/W3186065094","https://openalex.org/W4287263085","https://openalex.org/W3093803318","https://openalex.org/W3204418343"],"abstract_inverted_index":{"The":[0,153,184],"purpose":[1],"of":[2,95],"this":[3,62,64],"article":[4,65],"is":[5,86,115,176,202],"to":[6,29,76,88,98,103,137,148,204],"address":[7,77],"unsupervised":[8],"domain":[9,16,21,73,125,227],"adaptation":[10,74,228],"(UDA)":[11],"where":[12,162],"a":[13,67,82,111,121,134,141,145],"labeled":[14,169],"source":[15,142,164,170],"and":[17,119,144,172],"an":[18,199],"unlabeled":[19],"target":[20,146,174,181],"are":[22,156],"given.":[23],"Recent":[24],"advanced":[25],"UDA":[26],"methods":[27],"attempt":[28],"remove":[30],"domain-specific":[31,35,90],"properties":[32],"by":[33],"separating":[34],"information":[36],"from":[37,167,178],"domain-invariant":[38,59,160],"representations,":[39,161],"which":[40,126],"heavily":[41],"rely":[42],"on":[43,159,213],"the":[44,78,124,163,168,173,179,191,221,225],"designed":[45,157],"neural":[46],"network":[47,85,97],"structures.":[48],"Meanwhile,":[49,198],"they":[50],"do":[51],"not":[52],"consider":[53],"class":[54,150],"discriminate":[55,151],"representations":[56],"when":[57],"learning":[58],"representations.":[60,152],"To":[61],"end,":[63],"proposes":[66],"co-training":[68,135],"framework":[69],"for":[70,123],"heterogeneous":[71,83],"heuristic":[72,84,96],"(CO-HHDA)":[75],"above":[79],"issues.":[80],"First,":[81],"introduced":[87],"model":[89],"characters.":[91],"It":[92],"allows":[93],"structures":[94],"be":[99],"different":[100],"between":[101,117],"domains":[102,118],"avoid":[104],"underfitting":[105],"or":[106],"overfitting.":[107],"Specially,":[108],"we":[109,132],"initialize":[110],"small":[112],"structure":[113],"that":[114,220],"shared":[116],"increase":[120],"subnetwork":[122],"preserves":[127],"rich":[128],"specific":[129],"information.":[130],"Second,":[131],"propose":[133],"scheme":[136],"train":[138],"two":[139,154,185],"classifiers,":[140],"classifier":[143,165,175],"classifier,":[147],"enhance":[149],"classifiers":[155,186],"based":[158],"learns":[166],"data,":[171],"trained":[177],"generated":[180],"pseudolabeled":[182,196],"data.":[183,197],"teach":[187],"each":[188,209],"other":[189],"in":[190,208],"training":[192],"process":[193],"with":[194],"high-quality":[195],"adaptive":[200],"threshold":[201],"presented":[203],"select":[205],"reliable":[206],"pseudolabels":[207],"classifier.":[210],"Empirical":[211],"results":[212],"three":[214],"commonly":[215],"used":[216],"benchmark":[217],"datasets":[218],"demonstrate":[219],"proposed":[222],"CO-HHDA":[223],"outperforms":[224],"state-of-the-art":[226],"methods.":[229]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}
