{"id":"https://openalex.org/W4323520946","doi":"https://doi.org/10.1109/ieeeconf56349.2022.10052012","title":"Domain-Invariant Feature Alignment Using Variational Inference for Partial Domain Adaptation","display_name":"Domain-Invariant Feature Alignment Using Variational Inference for Partial Domain Adaptation","publication_year":2022,"publication_date":"2022-10-31","ids":{"openalex":"https://openalex.org/W4323520946","doi":"https://doi.org/10.1109/ieeeconf56349.2022.10052012"},"language":"en","primary_location":{"id":"doi:10.1109/ieeeconf56349.2022.10052012","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ieeeconf56349.2022.10052012","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 56th Asilomar Conference on Signals, Systems, and Computers","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/A5110736288","display_name":"Sandipan Choudhuri","orcid":null},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Sandipan Choudhuri","raw_affiliation_strings":["Arizona State University"],"affiliations":[{"raw_affiliation_string":"Arizona State University","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063263254","display_name":"Suli Adeniye","orcid":null},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Suli Adeniye","raw_affiliation_strings":["Arizona State University"],"affiliations":[{"raw_affiliation_string":"Arizona State University","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112853639","display_name":"Arunabha Sen","orcid":"https://orcid.org/0000-0002-5795-3465"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Arunabha Sen","raw_affiliation_strings":["Arizona State University"],"affiliations":[{"raw_affiliation_string":"Arizona State University","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089498346","display_name":"Hemanth Venkateswara","orcid":"https://orcid.org/0000-0002-3832-0881"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hemanth Venkateswara","raw_affiliation_strings":["Arizona State University"],"affiliations":[{"raw_affiliation_string":"Arizona State University","institution_ids":["https://openalex.org/I55732556"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5110736288"],"corresponding_institution_ids":["https://openalex.org/I55732556"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.16385936,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"8","issue":null,"first_page":"349","last_page":"355"},"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9563999772071838,"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"}},{"id":"https://openalex.org/T10515","display_name":"Cancer-related molecular mechanisms research","score":0.9501000046730042,"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/computer-science","display_name":"Computer science","score":0.7184813618659973},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.6030066609382629},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.5801833868026733},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5727829933166504},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5282372832298279},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.5276654362678528},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.515286922454834},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5009357929229736},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.49283480644226074},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4044291377067566},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38392820954322815},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3518978953361511},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3506912589073181},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.326302707195282},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15309134125709534}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7184813618659973},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.6030066609382629},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.5801833868026733},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5727829933166504},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5282372832298279},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.5276654362678528},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.515286922454834},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5009357929229736},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.49283480644226074},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4044291377067566},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38392820954322815},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3518978953361511},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3506912589073181},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.326302707195282},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15309134125709534},{"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.0},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ieeeconf56349.2022.10052012","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ieeeconf56349.2022.10052012","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 56th Asilomar Conference on Signals, Systems, and Computers","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W189742998","https://openalex.org/W1722318740","https://openalex.org/W1731081199","https://openalex.org/W1959608418","https://openalex.org/W2108598243","https://openalex.org/W2115699968","https://openalex.org/W2161381512","https://openalex.org/W2194775991","https://openalex.org/W2593768305","https://openalex.org/W2616966451","https://openalex.org/W2627183927","https://openalex.org/W2805760974","https://openalex.org/W2885722640","https://openalex.org/W2935849356","https://openalex.org/W2948527806","https://openalex.org/W2962835731","https://openalex.org/W2962986791","https://openalex.org/W2964109570","https://openalex.org/W2981885563","https://openalex.org/W3023747762","https://openalex.org/W3119539601","https://openalex.org/W3123982987","https://openalex.org/W3130367234","https://openalex.org/W3169562163","https://openalex.org/W4212774754","https://openalex.org/W4299518610","https://openalex.org/W4311243152","https://openalex.org/W6607672814","https://openalex.org/W6637618735","https://openalex.org/W6639480849","https://openalex.org/W6640963894","https://openalex.org/W6677245018","https://openalex.org/W6682132143","https://openalex.org/W6683633756","https://openalex.org/W6695692224","https://openalex.org/W6725448924"],"related_works":["https://openalex.org/W2055243143","https://openalex.org/W3201126466","https://openalex.org/W2807251790","https://openalex.org/W4282827391","https://openalex.org/W4321636575","https://openalex.org/W1986418932","https://openalex.org/W2357796999","https://openalex.org/W2045526782","https://openalex.org/W3095487414","https://openalex.org/W2901026139"],"abstract_inverted_index":{"The":[0,133],"standard":[1],"closed-set":[2],"domain":[3,31,41,88],"adaptation":[4,42],"approaches":[5],"seek":[6],"to":[7,85,102,117,151],"mitigate":[8],"distribution":[9,120],"discrepancies":[10],"between":[11],"two":[12],"domains":[13],"under":[14],"the":[15,63,68,86,124,130,143],"constraint":[16],"of":[17,46,126],"both":[18],"sharing":[19],"identical":[20,33,52],"label":[21,34,53,65,70],"sets.":[22],"However,":[23],"in":[24,136],"realistic":[25],"scenarios,":[26],"finding":[27],"an":[28],"optimal":[29],"source":[30,64,87,131],"with":[32,51,82,113],"space":[35,54],"is":[36],"a":[37,48,58,75,114],"challenging":[38],"task.":[39],"Partial":[40],"alleviates":[43],"this":[44,98],"problem":[45],"procuring":[47],"labeled":[49],"dataset":[50],"assumptions":[55],"and":[56,93,110,122,148],"addresses":[57],"more":[59],"practical":[60],"scenario":[61],"where":[62],"set":[66],"subsumes":[67],"target":[69],"set.":[71],"This,":[72],"however,":[73],"presents":[74],"few":[76],"additional":[77],"obstacles":[78],"during":[79],"adaptation.":[80],"Samples":[81],"categories":[83],"private":[84],"thwart":[89],"relevant":[90],"knowledge":[91],"transfer":[92,125],"degrade":[94],"model":[95],"performance.":[96],"In":[97],"work,":[99],"we":[100],"try":[101],"address":[103],"these":[104],"issues":[105],"by":[106],"coupling":[107],"variational":[108],"information":[109,128],"adversarial":[111],"learning":[112],"pseudo-labeling":[115],"technique":[116,145],"enforce":[118],"class":[119],"alignment":[121],"minimize":[123],"superfluous":[127],"from":[129],"samples.":[132],"experimental":[134],"findings":[135],"numerous":[137],"cross-domain":[138],"classification":[139],"tasks":[140],"demonstrate":[141],"that":[142],"proposed":[144],"delivers":[146],"superior":[147],"comparable":[149],"accuracy":[150],"existing":[152],"methods.":[153]},"counts_by_year":[],"updated_date":"2025-12-21T23:12:01.093139","created_date":"2025-10-10T00:00:00"}
