{"id":"https://openalex.org/W3138160896","doi":"https://doi.org/10.1109/bigdata50022.2020.9378021","title":"Virtual Adversarial Active Learning","display_name":"Virtual Adversarial Active Learning","publication_year":2020,"publication_date":"2020-12-10","ids":{"openalex":"https://openalex.org/W3138160896","doi":"https://doi.org/10.1109/bigdata50022.2020.9378021","mag":"3138160896"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata50022.2020.9378021","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata50022.2020.9378021","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Big Data (Big Data)","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/A5006621929","display_name":"Chin-Feng Yu","orcid":"https://orcid.org/0000-0003-1516-1782"},"institutions":[{"id":"https://openalex.org/I154864474","display_name":"National Taiwan University of Science and Technology","ror":"https://ror.org/00q09pe49","country_code":"TW","type":"education","lineage":["https://openalex.org/I154864474"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Chin-Feng Yu","raw_affiliation_strings":["National Taiwan University of Science and Technology,Department of Computer Science and Information Engineering,Taipei,Taiwan"],"affiliations":[{"raw_affiliation_string":"National Taiwan University of Science and Technology,Department of Computer Science and Information Engineering,Taipei,Taiwan","institution_ids":["https://openalex.org/I154864474"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030897009","display_name":"Hsing-Kuo Pao","orcid":"https://orcid.org/0000-0002-5518-9475"},"institutions":[{"id":"https://openalex.org/I154864474","display_name":"National Taiwan University of Science and Technology","ror":"https://ror.org/00q09pe49","country_code":"TW","type":"education","lineage":["https://openalex.org/I154864474"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Hsing-Kuo Pao","raw_affiliation_strings":["National Taiwan University of Science and Technology,Department of Computer Science and Information Engineering,Taipei,Taiwan"],"affiliations":[{"raw_affiliation_string":"National Taiwan University of Science and Technology,Department of Computer Science and Information Engineering,Taipei,Taiwan","institution_ids":["https://openalex.org/I154864474"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5006621929"],"corresponding_institution_ids":["https://openalex.org/I154864474"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.21607915,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"52","issue":null,"first_page":"5323","last_page":"5331"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9998999834060669,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9998999834060669,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9853000044822693,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9807999730110168,"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/oracle","display_name":"Oracle","score":0.8745496869087219},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7656484246253967},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.7186427712440491},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7020359039306641},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6298908591270447},{"id":"https://openalex.org/keywords/active-learning","display_name":"Active learning (machine learning)","score":0.5982383489608765},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5900384187698364},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.4891805946826935}],"concepts":[{"id":"https://openalex.org/C55166926","wikidata":"https://www.wikidata.org/wiki/Q2892946","display_name":"Oracle","level":2,"score":0.8745496869087219},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7656484246253967},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.7186427712440491},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7020359039306641},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6298908591270447},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.5982383489608765},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5900384187698364},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.4891805946826935},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata50022.2020.9378021","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata50022.2020.9378021","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.5400000214576721,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320309618","display_name":"Ministry of Science and Technology","ror":"https://ror.org/02b207r52"},{"id":"https://openalex.org/F4320323900","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W769612788","https://openalex.org/W1580375566","https://openalex.org/W1665214252","https://openalex.org/W1673923490","https://openalex.org/W1845402413","https://openalex.org/W1945616565","https://openalex.org/W2085989833","https://openalex.org/W2097117768","https://openalex.org/W2110910681","https://openalex.org/W2122860281","https://openalex.org/W2128518360","https://openalex.org/W2163605009","https://openalex.org/W2165484066","https://openalex.org/W2243397390","https://openalex.org/W2343514605","https://openalex.org/W2460937040","https://openalex.org/W2788686132","https://openalex.org/W2903158431","https://openalex.org/W2914331073","https://openalex.org/W2949103145","https://openalex.org/W2951911250","https://openalex.org/W2963207607","https://openalex.org/W2964040467","https://openalex.org/W2964153729","https://openalex.org/W2964159205","https://openalex.org/W2964350391","https://openalex.org/W4206723194","https://openalex.org/W4300511536","https://openalex.org/W6622262455","https://openalex.org/W6637162671","https://openalex.org/W6637242042","https://openalex.org/W6638701278","https://openalex.org/W6640425456","https://openalex.org/W6653695713","https://openalex.org/W6684191040","https://openalex.org/W6694260854","https://openalex.org/W6719080892","https://openalex.org/W6733049761","https://openalex.org/W6736346607","https://openalex.org/W6748034479","https://openalex.org/W6756615331"],"related_works":["https://openalex.org/W2133845513","https://openalex.org/W2056314584","https://openalex.org/W1492505081","https://openalex.org/W1986633584","https://openalex.org/W2976807053","https://openalex.org/W184546935","https://openalex.org/W2909115059","https://openalex.org/W2943886396","https://openalex.org/W2949671220","https://openalex.org/W42414577"],"abstract_inverted_index":{"In":[0,244],"traditional":[1],"active":[2,130,223,272],"learning,":[3],"one":[4,49,73],"of":[5,74,91,156,162],"the":[6,13,31,36,39,48,54,75,94,100,123,137,154,164,170,175,190,207,213,222,230,248,268,279,285],"most":[7,14,25],"well-known":[8,293],"strategies":[9],"is":[10,81],"to":[11,60,86,116,121,169,205,221],"select":[12,174],"uncertain":[15],"data":[16,57,165,176,208,232],"for":[17,83,271],"annotation.":[18],"By":[19],"doing":[20],"that,":[21],"we":[22,27,98,126,173,227,246],"acquire":[23],"as":[24,26,256],"can":[28,42,134,202,251,283],"obtain":[29],"from":[30,50,241],"labeling":[32,231],"oracle":[33],"so":[34],"that":[35,133,166,177,233,250,278],"training":[37,105],"in":[38,102,180],"next":[40],"run":[41,52],"be":[43,67,254],"much":[44],"more":[45],"effective":[46],"than":[47],"this":[51],"once":[53,237],"informative":[55],"labeled":[56],"are":[58,167,178,239],"added":[59],"training.":[61],"The":[62,193],"strategy":[63,132,146,195,282],"however,":[64],"may":[65],"not":[66,252],"suitable":[68],"when":[69],"deep":[70,103,124],"learning":[71,80,104,131,224,273],"become":[72],"dominant":[76],"modeling":[77],"techniques.":[78],"Deep":[79],"notorious":[82],"its":[84],"failure":[85],"achieve":[87],"a":[88,110,142,181,257],"certain":[89],"degree":[90],"effectiveness":[92],"under":[93],"adversarial":[95,119],"environment.":[96],"Often":[97],"see":[99],"sparsity":[101],"space":[106],"which":[107],"gives":[108],"us":[109,204,263],"result":[111],"with":[112,136,183,209,215],"low":[113],"confidence.":[114],"Moreover,":[115,226],"have":[117,128,247],"some":[118],"inputs":[120],"fool":[122],"learners,":[125],"should":[127],"an":[129,242],"deal":[135],"aforementioned":[138],"difficulties.":[139],"We":[140],"propose":[141],"novel":[143],"Active":[144,199],"Learning":[145,200],"based":[147],"on":[148,291],"Virtual":[149,197],"Adversarial":[150,198],"Training":[151],"(VAT)":[152],"and":[153,265],"computation":[155],"local":[157],"distributional":[158],"roughness":[159],"(LDR).":[160],"Instead":[161],"selecting":[163],"closest":[168],"decision":[171],"boundaries,":[172],"located":[179],"place":[182],"rough":[184,210],"enough":[185,235],"surface":[186],"if":[187],"measured":[188],"by":[189],"posterior":[191,217],"probability.":[192],"proposed":[194,280],"called":[196],"(VAAL)":[201],"help":[203],"find":[206],"surface,":[211],"reshape":[212],"model":[214,288],"smooth":[216],"distribution":[218],"output":[219],"thanks":[220],"framework.":[225],"shall":[228],"prefer":[229],"own":[234],"confidence":[236],"they":[238],"annotated":[240],"oracle.":[243],"VAAL,":[245],"VAT":[249],"only":[253],"used":[255],"regularization":[258],"term":[259],"but":[260],"also":[261],"helps":[262],"effectively":[264],"actively":[266],"choose":[267],"valuable":[269],"samples":[270],"labeling.":[274],"Experiment":[275],"results":[276],"show":[277],"VAAL":[281],"guide":[284],"convolutional":[286],"networks":[287],"converging":[289],"efficiently":[290],"several":[292],"datasets.":[294]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}