乐胖代购免代理版

{"id":"https://openalex.org/W3114997198","doi":"https://doi.org/10.1145/3430984.3431017","title":"Deep Domain Adaptation under Label Scarcity","display_name":"Deep Domain Adaptation under Label Scarcity","publication_year":2020,"publication_date":"2020-12-28","ids":{"openalex":"https://openalex.org/W3114997198","doi":"https://doi.org/10.1145/3430984.3431017","mag":"3114997198"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1145/3430984.3431017","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5081896052","display_name":"Amar Prakash Azad","orcid":null},"institutions":[{"id":"https://openalex.org/I4210103279","display_name":"IBM Research - India","ror":"https://ror.org/014wt7r80","country_code":"IN","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210103279","https://openalex.org/I4210114115"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Amar Prakash Azad","raw_affiliation_strings":["IBM Research Lab, India"],"affiliations":[{"raw_affiliation_string":"IBM Research Lab, India","institution_ids":["https://openalex.org/I4210103279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109547753","display_name":"Dinesh Garg","orcid":null},"institutions":[{"id":"https://openalex.org/I4210103279","display_name":"IBM Research - India","ror":"https://ror.org/014wt7r80","country_code":"IN","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210103279","https://openalex.org/I4210114115"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Dinesh Garg","raw_affiliation_strings":["IBM Research Lab, India"],"affiliations":[{"raw_affiliation_string":"IBM Research Lab, India","institution_ids":["https://openalex.org/I4210103279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038482152","display_name":"Priyanka Agrawal","orcid":"https://orcid.org/0000-0003-1314-7143"},"institutions":[{"id":"https://openalex.org/I4210103279","display_name":"IBM Research - India","ror":"https://ror.org/014wt7r80","country_code":"IN","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210103279","https://openalex.org/I4210114115"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Priyanka Agrawal","raw_affiliation_strings":["IBM Research Lab, India"],"affiliations":[{"raw_affiliation_string":"IBM Research Lab, India","institution_ids":["https://openalex.org/I4210103279"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045127324","display_name":"Arun Kumar","orcid":"https://orcid.org/0000-0002-4309-3396"},"institutions":[{"id":"https://openalex.org/I4210103279","display_name":"IBM Research - India","ror":"https://ror.org/014wt7r80","country_code":"IN","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210103279","https://openalex.org/I4210114115"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Arun Kumar","raw_affiliation_strings":["IBM Research Lab, India"],"affiliations":[{"raw_affiliation_string":"IBM Research Lab, India","institution_ids":["https://openalex.org/I4210103279"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":60},"biblio":{"volume":null,"issue":null,"first_page":"101","last_page":"109"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9993,"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":0.9993,"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":0.9808,"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/T10028","display_name":"Topic Modeling","score":0.9289,"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/domain-adaptation","display_name":"Domain Adaptation","score":0.88960445},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.80567294},{"id":"https://openalex.org/keywords/scarcity","display_name":"Scarcity","score":0.6289399}],"concepts":[{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.88960445},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.80567294},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7896969},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.70357907},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.69981724},{"id":"https://openalex.org/C109747225","wikidata":"https://www.wikidata.org/wiki/Q815758","display_name":"Scarcity","level":2,"score":0.6289399},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5800519},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5701294},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5617549},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.5346673},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.060818255},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.05610609},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C175444787","wikidata":"https://www.wikidata.org/wiki/Q39072","display_name":"Microeconomics","level":1,"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/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1145/3430984.3431017","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4,"display_name":"Quality education","id":"https://metadata.un.org/sdg/4"}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":19,"referenced_works":["https://openalex.org/W1731081199","https://openalex.org/W1982696459","https://openalex.org/W2033547469","https://openalex.org/W2034368206","https://openalex.org/W2083544878","https://openalex.org/W2104094955","https://openalex.org/W2120615054","https://openalex.org/W2250539671","https://openalex.org/W2251189452","https://openalex.org/W2512531235","https://openalex.org/W2560674852","https://openalex.org/W2786808285","https://openalex.org/W2930957955","https://openalex.org/W2962897020","https://openalex.org/W2963424663","https://openalex.org/W2997617958","https://openalex.org/W3035944493","https://openalex.org/W3142239405","https://openalex.org/W4297969478"],"related_works":["https://openalex.org/W4310988119","https://openalex.org/W4297672492","https://openalex.org/W4283211831","https://openalex.org/W4246396837","https://openalex.org/W3191453585","https://openalex.org/W3126451824","https://openalex.org/W2798287483","https://openalex.org/W2502115930","https://openalex.org/W2482350142","https://openalex.org/W1561927205"],"abstract_inverted_index":{"The":[0],"goal":[1],"behind":[2],"Domain":[3],"Adaptation":[4],"(DA)":[5],"is":[6],"to":[7,16,69,119,123],"leverage":[8],"the":[9,34,75,90,124,144],"labeled":[10,67],"examples":[11,68],"from":[12],"a":[13,22,40,52,62,71,121,140],"source":[14,66],"domain":[15,24],"infer":[17,70],"an":[18,105],"accurate":[19],"model":[20,73],"for":[21,48,74],"target":[23,76],"where":[25],"labels":[26],"are":[27],"not":[28],"available":[29],"or":[30],"in":[31,42,143],"scarce":[32,99,154],"at":[33],"best.":[35],"Recently,":[36],"there":[37],"has":[38],"been":[39],"surge":[41],"adversarial":[43],"learning":[44,112,116],"based":[45],"deep-net":[46],"approaches":[47,94,128,149],"DA":[49],"problem":[50],"\u2013":[51],"prominent":[53],"example":[54],"being":[55],"DANN":[56,152],"approach":[57],"[9].":[58],"These":[59],"methods":[60],"require":[61],"large":[63],"number":[64],"of":[65,92,126,146],"good":[72],"domain;":[77],"but":[78],"start":[79],"performing":[80],"poorly":[81],"with":[82,114],"reduced":[83],"labels.":[84],"In":[85],"this":[86],"paper,":[87],"we":[88,103],"study":[89],"behavior":[91],"such":[93,98,150],"(especially":[95],"DANN)":[96],"under":[97,129,153],"label":[100,130,155],"scenarios.":[101,156],"Further,":[102],"propose":[104],"architecture,":[106],"namely":[107],"TRAVERS,":[108],"that":[109],"amalgamates":[110],"TRAnsductive":[111],"principles":[113],"adVERSarial":[115],"so":[117],"as":[118,151],"provide":[120],"cushion":[122],"performance":[125,145],"these":[127],"scarcity.":[131],"Experimental":[132],"results":[133],"(both":[134],"on":[135],"text":[136],"and":[137],"images)":[138],"show":[139],"significant":[141],"boost":[142],"TRAVERS":[147],"over":[148]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W3114997198","counts_by_year":[],"updated_date":"2024-12-26T07:31:54.851486","created_date":"2021-01-05"}