{"id":"https://openalex.org/W3015818151","doi":"https://doi.org/10.1109/icassp40776.2020.9053310","title":"Adversarial Mixup Synthesis Training for Unsupervised Domain Adaptation","display_name":"Adversarial Mixup Synthesis Training for Unsupervised Domain Adaptation","publication_year":2020,"publication_date":"2020-04-09","ids":{"openalex":"https://openalex.org/W3015818151","doi":"https://doi.org/10.1109/icassp40776.2020.9053310","mag":"3015818151"},"language":"en","primary_location":{"id":"doi:10.1109/icassp40776.2020.9053310","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9053310","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5065371644","display_name":"Yuhua Tang","orcid":"https://orcid.org/0000-0002-4956-3379"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuhua Tang","raw_affiliation_strings":["State Key Laboratory of High Performance Computing, College of Computer, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of High Performance Computing, College of Computer, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088132719","display_name":"Zhipeng Lin","orcid":"https://orcid.org/0000-0001-5941-2163"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhipeng Lin","raw_affiliation_strings":["State Key Laboratory of High Performance Computing, College of Computer, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of High Performance Computing, College of Computer, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069527951","display_name":"Haotian Wang","orcid":"https://orcid.org/0000-0002-0362-181X"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haotian Wang","raw_affiliation_strings":["State Key Laboratory of High Performance Computing, College of Computer, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of High Performance Computing, College of Computer, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101897932","display_name":"Liyang Xu","orcid":"https://orcid.org/0000-0003-0932-643X"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liyang Xu","raw_affiliation_strings":["State Key Laboratory of High Performance Computing, College of Computer, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of High Performance Computing, College of Computer, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5065371644"],"corresponding_institution_ids":["https://openalex.org/I170215575"],"apc_list":null,"apc_paid":null,"fwci":0.6628,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.75062259,"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":"3727","last_page":"3731"},"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":0.9991000294685364,"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":0.9991000294685364,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9369999766349792,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9345999956130981,"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/adversarial-system","display_name":"Adversarial system","score":0.8082032203674316},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8008496761322021},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.6504863500595093},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6062425971031189},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5935178995132446},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5824471712112427},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5776745080947876},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.5403135418891907},{"id":"https://openalex.org/keywords/divergence","display_name":"Divergence (linguistics)","score":0.5373936891555786},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.500889778137207},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.4824972152709961},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.4823255240917206},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.46408817172050476},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.44790786504745483},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11483824253082275},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.08024418354034424}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.8082032203674316},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8008496761322021},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6504863500595093},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6062425971031189},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5935178995132446},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5824471712112427},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5776745080947876},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5403135418891907},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.5373936891555786},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.500889778137207},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.4824972152709961},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.4823255240917206},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.46408817172050476},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.44790786504745483},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11483824253082275},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.08024418354034424},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","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/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","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/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"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/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/icassp40776.2020.9053310","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9053310","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W1731081199","https://openalex.org/W2059979378","https://openalex.org/W2099471712","https://openalex.org/W2104094955","https://openalex.org/W2159291411","https://openalex.org/W2478454054","https://openalex.org/W2511131004","https://openalex.org/W2551835155","https://openalex.org/W2584009249","https://openalex.org/W2592691248","https://openalex.org/W2593634001","https://openalex.org/W2594718649","https://openalex.org/W2683470288","https://openalex.org/W2765407302","https://openalex.org/W2786559811","https://openalex.org/W2890336707","https://openalex.org/W2897355816","https://openalex.org/W2921320475","https://openalex.org/W2921861056","https://openalex.org/W2950635901","https://openalex.org/W2951970475","https://openalex.org/W2952411227","https://openalex.org/W2953070460","https://openalex.org/W2953127297","https://openalex.org/W2962687275","https://openalex.org/W2962970380","https://openalex.org/W2963399829","https://openalex.org/W2963449430","https://openalex.org/W2964041944","https://openalex.org/W2964116600","https://openalex.org/W2964159205","https://openalex.org/W2964160479","https://openalex.org/W2964184826","https://openalex.org/W2965912480","https://openalex.org/W4288320878","https://openalex.org/W4293469690","https://openalex.org/W4297749952","https://openalex.org/W4300833946","https://openalex.org/W4320013936","https://openalex.org/W6637618735","https://openalex.org/W6683633756","https://openalex.org/W6725448924","https://openalex.org/W6729906282","https://openalex.org/W6730389898","https://openalex.org/W6733814495","https://openalex.org/W6735050833","https://openalex.org/W6736346607","https://openalex.org/W6745136726","https://openalex.org/W6745986955","https://openalex.org/W6748312029","https://openalex.org/W6754528357","https://openalex.org/W6755310938","https://openalex.org/W6760184523","https://openalex.org/W6760606919","https://openalex.org/W6764051988"],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W2482350142","https://openalex.org/W4246396837","https://openalex.org/W3126451824","https://openalex.org/W1561927205","https://openalex.org/W3191453585","https://openalex.org/W4297672492","https://openalex.org/W4310988119","https://openalex.org/W4285226279","https://openalex.org/W4288019534"],"abstract_inverted_index":{"Domain":[0,9],"adversarial":[1,16],"training":[2,17,58],"is":[3],"a":[4,27,41,107],"popular":[5],"approach":[6,43],"for":[7],"Unsupervised":[8],"Adaptation":[10],"(DA).":[11],"However,":[12],"the":[13,23,52,57,79,102,130],"transferability":[14],"of":[15,67,98,134],"framework":[18],"may":[19],"drop":[20],"greatly":[21],"on":[22,88,101,110,126,142],"adaptation":[24],"tasks":[25],"with":[26,59,95],"large":[28],"distribution":[29],"divergence":[30],"between":[31,65],"source":[32],"and":[33,70,116,132],"target":[34],"domains.":[35],"In":[36],"this":[37,75,111],"paper,":[38],"we":[39,105],"propose":[40],"new":[42],"termed":[44],"Adversarial":[45],"Mixup":[46],"Synthesis":[47],"Training":[48],"(AMST)":[49],"to":[50,81],"alleviate":[51],"issue.":[53],"The":[54],"AMST":[55,77,119],"augments":[56],"synthesis":[60],"samples":[61],"by":[62],"linearly":[63],"interpolating":[64],"pairs":[66],"hidden":[68],"representations":[69,94],"their":[71],"domain":[72,84],"labels.":[73],"By":[74],"means,":[76],"encourages":[78],"model":[80],"make":[82],"consistency":[83],"prediction":[85],"less":[86],"confidently":[87],"interpolations":[89],"points,":[90],"which":[91],"learn":[92],"domain-specific":[93],"fewer":[96],"directions":[97],"variance.":[99],"Based":[100],"previous":[103],"work,":[104],"conduct":[106],"theoretical":[108],"analysis":[109],"phenomenon":[112],"under":[113],"ideal":[114],"conditions":[115],"show":[117],"that":[118],"could":[120],"improve":[121],"generalization":[122],"ability.":[123],"Finally,":[124],"experiments":[125],"benchmark":[127],"dataset":[128],"demonstrate":[129],"effectiveness":[131],"practicability":[133],"AMST.":[135],"We":[136],"will":[137],"publicly":[138],"release":[139],"our":[140],"code":[141],"github":[143],"soon.":[144]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}