{"id":"https://openalex.org/W4404037470","doi":"https://doi.org/10.1109/mlsp58920.2024.10734808","title":"Heterogeneous Tensor Domain Adaptation","display_name":"Heterogeneous Tensor Domain Adaptation","publication_year":2024,"publication_date":"2024-09-22","ids":{"openalex":"https://openalex.org/W4404037470","doi":"https://doi.org/10.1109/mlsp58920.2024.10734808"},"language":"en","primary_location":{"id":"doi:10.1109/mlsp58920.2024.10734808","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/mlsp58920.2024.10734808","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 34th International Workshop on Machine Learning for Signal Processing (MLSP)","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/A5000740943","display_name":"Yicong He","orcid":"https://orcid.org/0000-0003-3398-3376"},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yicong He","raw_affiliation_strings":["University of Central Florida,Department of Electrical and Computer Engineering,Orlando,FL,USA,32816"],"affiliations":[{"raw_affiliation_string":"University of Central Florida,Department of Electrical and Computer Engineering,Orlando,FL,USA,32816","institution_ids":["https://openalex.org/I106165777"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003612688","display_name":"George Atia","orcid":"https://orcid.org/0000-0001-7958-9855"},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"George K. Atia","raw_affiliation_strings":["University of Central Florida,Department of Electrical and Computer Engineering,Orlando,FL,USA,32816"],"affiliations":[{"raw_affiliation_string":"University of Central Florida,Department of Electrical and Computer Engineering,Orlando,FL,USA,32816","institution_ids":["https://openalex.org/I106165777"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5000740943"],"corresponding_institution_ids":["https://openalex.org/I106165777"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18562874,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9857000112533569,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9857000112533569,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13650","display_name":"Computational Physics and Python Applications","score":0.9171000123023987,"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":0.6680432558059692},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.5821036696434021},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.5679560303688049},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.4948672652244568},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.478061705827713},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2544378638267517},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1564941108226776},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.10786384344100952},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.060047030448913574},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.05961716175079346}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6680432558059692},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.5821036696434021},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.5679560303688049},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.4948672652244568},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.478061705827713},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2544378638267517},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1564941108226776},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.10786384344100952},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.060047030448913574},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.05961716175079346},{"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mlsp58920.2024.10734808","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/mlsp58920.2024.10734808","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 34th International Workshop on Machine Learning for Signal Processing (MLSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3049700353","display_name":null,"funder_award_id":"HROO11-24-9-0427","funder_id":"https://openalex.org/F4320332180","funder_display_name":"Defense Advanced Research Projects Agency"},{"id":"https://openalex.org/G4439686520","display_name":null,"funder_award_id":"CCF-2106339","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/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W46086471","https://openalex.org/W1963826206","https://openalex.org/W2025671805","https://openalex.org/W2086953401","https://openalex.org/W2096943734","https://openalex.org/W2115403315","https://openalex.org/W2125865219","https://openalex.org/W2141200867","https://openalex.org/W2170607218","https://openalex.org/W2422697180","https://openalex.org/W2519397578","https://openalex.org/W2593768305","https://openalex.org/W2605146283","https://openalex.org/W2889472764","https://openalex.org/W2892946488","https://openalex.org/W2963275094","https://openalex.org/W2964099118","https://openalex.org/W3005485628","https://openalex.org/W3182116573","https://openalex.org/W4210258547","https://openalex.org/W4226296924","https://openalex.org/W4388488870","https://openalex.org/W6755201857","https://openalex.org/W6763122499"],"related_works":["https://openalex.org/W4394775207","https://openalex.org/W4389474468","https://openalex.org/W2047382916","https://openalex.org/W4300172004","https://openalex.org/W2142176343","https://openalex.org/W3203792196","https://openalex.org/W4321649381","https://openalex.org/W2997645659","https://openalex.org/W3180787869","https://openalex.org/W2955455867"],"abstract_inverted_index":{"Heterogeneous":[0],"domain":[1,8,69,152],"adaptation":[2,9,70,153],"(HDA)":[3],"addresses":[4],"the":[5,13,28,51,76,124,133,156],"chal-lenge":[6],"of":[7,21,53,159],"in":[10,34,123,164],"scenarios":[11],"where":[12,72],"source":[14,77,134],"and":[15,31,136],"target":[16,79,138,142],"domains":[17],"exhibit":[18],"distinct":[19],"types":[20],"features.":[22],"While":[23],"nu-merous":[24],"studies":[25],"have":[26],"considered":[27],"HDA":[29,169],"problem":[30],"demon-strated":[32],"efficacy":[33],"transferring":[35],"knowledge":[36],"across":[37],"diverse":[38],"feature":[39,48,121],"types,":[40],"existing":[41,167],"methods":[42],"are":[43,81],"predominantly":[44],"tailored":[45],"for":[46],"I-D":[47],"vectors,":[49],"leaving":[50],"handling":[52],"high-order":[54],"features":[55,73,104],"largely":[56],"under-explored.":[57],"In":[58],"this":[59],"paper,":[60],"we":[61,112],"address":[62],"a":[63,91,106,114],"new":[64],"problem,":[65],"namely,":[66],"heterogeneous":[67,103],"tensor":[68,98,109,125],"(HTDA),":[71],"from":[74,131],"either":[75],"or":[78,86],"do-mains":[80],"tensors":[82],"with":[83],"different":[84],"sizes":[85],"orders.":[87],"Our":[88,147],"approach":[89],"involves":[90],"multilinear":[92],"principal":[93],"component":[94],"analysis":[95],"(MPCA)":[96],"based":[97],"projection":[99],"method":[100,163],"which":[101],"projects":[102],"onto":[105],"shared":[107],"latent":[108],"space.":[110],"Additionally,":[111],"leverage":[113],"probabilistic":[115],"class-wise":[116],"distribution":[117],"alignment":[118],"to":[119,140,166],"align":[120],"distributions":[122],"space,":[126],"followed":[127],"by":[128],"label":[129],"propagation":[130],"both":[132],"data":[135,139,143],"labeled":[137],"unlabeled":[141],"through":[144],"graph":[145],"regularization.":[146],"experimental":[148],"results":[149],"on":[150],"multiple":[151],"datasets":[154],"demonstrate":[155],"superior":[157],"performance":[158],"our":[160],"proposed":[161],"tensor-based":[162],"comparison":[165],"vector-based":[168],"methods.":[170]},"counts_by_year":[],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}
