{"id":"https://openalex.org/W3006767546","doi":"https://doi.org/10.1109/bigdata47090.2019.9006177","title":"Co-Representation Learning Framework For the Open-Set Data Classification","display_name":"Co-Representation Learning Framework For the Open-Set Data Classification","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W3006767546","doi":"https://doi.org/10.1109/bigdata47090.2019.9006177","mag":"3006767546"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata47090.2019.9006177","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata47090.2019.9006177","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 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/A5012907875","display_name":"Zhuoyi Wang","orcid":"https://orcid.org/0000-0002-1058-2791"},"institutions":[{"id":"https://openalex.org/I162577319","display_name":"The University of Texas at Dallas","ror":"https://ror.org/049emcs32","country_code":"US","type":"education","lineage":["https://openalex.org/I162577319"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Zhuoyi Wang","raw_affiliation_strings":["Department of Computer Science, The University of Texas at Dallas, Richardson, TX, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, The University of Texas at Dallas, Richardson, TX, USA","institution_ids":["https://openalex.org/I162577319"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035080566","display_name":"Bo Dong","orcid":"https://orcid.org/0000-0001-7695-9072"},"institutions":[{"id":"https://openalex.org/I162577319","display_name":"The University of Texas at Dallas","ror":"https://ror.org/049emcs32","country_code":"US","type":"education","lineage":["https://openalex.org/I162577319"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bo Dong","raw_affiliation_strings":["Department of Computer Science, The University of Texas at Dallas, Richardson, TX, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, The University of Texas at Dallas, Richardson, TX, USA","institution_ids":["https://openalex.org/I162577319"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058569122","display_name":"Yu Lin","orcid":"https://orcid.org/0000-0003-1131-6839"},"institutions":[{"id":"https://openalex.org/I162577319","display_name":"The University of Texas at Dallas","ror":"https://ror.org/049emcs32","country_code":"US","type":"education","lineage":["https://openalex.org/I162577319"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yu Lin","raw_affiliation_strings":["Department of Computer Science, The University of Texas at Dallas, Richardson, TX, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, The University of Texas at Dallas, Richardson, TX, USA","institution_ids":["https://openalex.org/I162577319"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039083934","display_name":"Yigong Wang","orcid":"https://orcid.org/0000-0002-0642-1477"},"institutions":[{"id":"https://openalex.org/I162577319","display_name":"The University of Texas at Dallas","ror":"https://ror.org/049emcs32","country_code":"US","type":"education","lineage":["https://openalex.org/I162577319"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yigong Wang","raw_affiliation_strings":["Department of Computer Science, The University of Texas at Dallas, Richardson, TX, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, The University of Texas at Dallas, Richardson, TX, USA","institution_ids":["https://openalex.org/I162577319"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072556986","display_name":"Md. Shihabul Islam","orcid":"https://orcid.org/0000-0002-8234-1153"},"institutions":[{"id":"https://openalex.org/I162577319","display_name":"The University of Texas at Dallas","ror":"https://ror.org/049emcs32","country_code":"US","type":"education","lineage":["https://openalex.org/I162577319"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Md Shihabul Islam","raw_affiliation_strings":["Department of Computer Science, The University of Texas at Dallas, Richardson, TX, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, The University of Texas at Dallas, Richardson, TX, USA","institution_ids":["https://openalex.org/I162577319"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005002693","display_name":"Latifur Khan","orcid":"https://orcid.org/0000-0002-9300-1576"},"institutions":[{"id":"https://openalex.org/I162577319","display_name":"The University of Texas at Dallas","ror":"https://ror.org/049emcs32","country_code":"US","type":"education","lineage":["https://openalex.org/I162577319"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Latifur Khan","raw_affiliation_strings":["Department of Computer Science, The University of Texas at Dallas, Richardson, TX, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, The University of Texas at Dallas, Richardson, TX, USA","institution_ids":["https://openalex.org/I162577319"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5012907875"],"corresponding_institution_ids":["https://openalex.org/I162577319"],"apc_list":null,"apc_paid":null,"fwci":1.2601,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.85657919,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"2011","issue":null,"first_page":"239","last_page":"244"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9984999895095825,"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/T10057","display_name":"Face and Expression Recognition","score":0.9930999875068665,"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/softmax-function","display_name":"Softmax function","score":0.9382914304733276},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7386852502822876},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7370049357414246},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6126770377159119},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.552811324596405},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.49070560932159424},{"id":"https://openalex.org/keywords/complement","display_name":"Complement (music)","score":0.4895568788051605},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.4701792299747467},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.45604801177978516},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.45383337140083313},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.45016252994537354},{"id":"https://openalex.org/keywords/open-set","display_name":"Open set","score":0.4483739137649536},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.437465101480484},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4034557640552521},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14100199937820435}],"concepts":[{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.9382914304733276},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7386852502822876},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7370049357414246},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6126770377159119},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.552811324596405},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.49070560932159424},{"id":"https://openalex.org/C112313634","wikidata":"https://www.wikidata.org/wiki/Q7886648","display_name":"Complement (music)","level":5,"score":0.4895568788051605},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.4701792299747467},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.45604801177978516},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.45383337140083313},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.45016252994537354},{"id":"https://openalex.org/C42357961","wikidata":"https://www.wikidata.org/wiki/Q213363","display_name":"Open set","level":2,"score":0.4483739137649536},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.437465101480484},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4034557640552521},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14100199937820435},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C188082640","wikidata":"https://www.wikidata.org/wiki/Q1780899","display_name":"Complementation","level":4,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C127716648","wikidata":"https://www.wikidata.org/wiki/Q104053","display_name":"Phenotype","level":3,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata47090.2019.9006177","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata47090.2019.9006177","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Big Data (Big Data)","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/W1821462560","https://openalex.org/W2096733369","https://openalex.org/W2112796928","https://openalex.org/W2117154949","https://openalex.org/W2130416896","https://openalex.org/W2138621090","https://openalex.org/W2160815625","https://openalex.org/W2187089797","https://openalex.org/W2194775991","https://openalex.org/W2335728318","https://openalex.org/W2434851943","https://openalex.org/W2470412537","https://openalex.org/W2531327146","https://openalex.org/W2604735226","https://openalex.org/W2750384547","https://openalex.org/W2767216538","https://openalex.org/W2767414122","https://openalex.org/W2805937249","https://openalex.org/W2907228390","https://openalex.org/W2951761524","https://openalex.org/W2963026686","https://openalex.org/W2963149653","https://openalex.org/W2963693742","https://openalex.org/W2963924212","https://openalex.org/W3099206234","https://openalex.org/W3118608800","https://openalex.org/W6638523607","https://openalex.org/W6677328822","https://openalex.org/W6680272447","https://openalex.org/W6703116779","https://openalex.org/W6719935260","https://openalex.org/W6728622933","https://openalex.org/W6736270679","https://openalex.org/W6743688258","https://openalex.org/W6745891213","https://openalex.org/W6787972765"],"related_works":["https://openalex.org/W2743258233","https://openalex.org/W4307834408","https://openalex.org/W4320925816","https://openalex.org/W2890619523","https://openalex.org/W3120400911","https://openalex.org/W3208883981","https://openalex.org/W2771515600","https://openalex.org/W2900180889","https://openalex.org/W1679711741","https://openalex.org/W3176035184"],"abstract_inverted_index":{"Deep":[0],"Neural":[1],"Network":[2],"(DNN)":[3],"has":[4],"been":[5],"largely":[6],"demonstrated":[7],"to":[8,25,116,142,175,184,207],"be":[9],"effective":[10],"for":[11,34,109],"real-world":[12,73],"classification":[13,84,187],"problems.":[14],"However,":[15],"such":[16,77],"model":[17,39,112],"requires":[18],"a":[19,98,111,136],"huge":[20],"amount":[21],"of":[22,124,203],"training":[23,36,110],"samples":[24,32,108],"get":[26],"more":[27],"accurate":[28],"result.":[29],"When":[30],"limited":[31,107],"allowed":[33],"the":[35,38,46,51,57,79,122,152,167,172,186,201],"step,":[37],"may":[40,54],"perform":[41],"weak":[42],"generalization":[43,146],"ability":[44],"on":[45,91,171,197],"test":[47,58],"set,":[48],"especially":[49],"when":[50],"novel/unseen":[52],"class":[53,126,190],"occur":[55],"during":[56],"period":[59],"(we":[60],"call":[61],"it":[62,115],"open-set":[63,80],"classification).":[64],"This":[65],"severely":[66],"limits":[67],"its":[68],"further":[69],"utility":[70],"in":[71,180],"many":[72],"large":[74],"scale":[75],"applications,":[76],"as":[78],"image":[81],"and":[82,120,147,157,188],"text":[83],"scenarios.":[85],"In":[86],"this":[87,93],"paper,":[88],"we":[89,134,165],"focus":[90],"addressing":[92],"key":[94,130],"challenge":[95],"by":[96],"developing":[97],"DNN":[99],"based":[100],"co-representation":[101],"learning":[102],"approach":[103],"RLCN.":[104],"It":[105],"utilizes":[106],"then":[113],"applies":[114],"classify":[117],"normal":[118],"instances":[119],"detect":[121],"emergence":[123],"novel":[125,189],"over":[127],"time.":[128],"The":[129],"novelty":[131],"is":[132],"that":[133],"design":[135],"weighted":[137],"pairwise-constraint":[138],"loss":[139],"(WPC)":[140],"function":[141,174],"learn":[143],"an":[144],"enhanced":[145],"robust":[148],"feature":[149],"embedding,":[150],"where":[151],"intra-class":[153],"(same":[154],"class)":[155,160],"compactness":[156],"inter-class":[158],"(different":[159],"separation":[161],"are":[162],"achieved.":[163],"Moreover,":[164],"apply":[166],"temperature":[168],"scaling":[169],"scheme":[170],"softmax":[173,178],"replace":[176],"traditional":[177],"output":[179],"our":[181,204],"open-world":[182],"classifier":[183],"achieve":[185],"detection":[191],"simultaneously.":[192],"Our":[193],"extensive":[194],"empirical":[195],"evaluation":[196],"benchmark":[198],"datasets":[199],"demonstrate":[200],"effectiveness":[202],"framework":[205],"compared":[206],"other":[208],"competing":[209],"techniques.":[210]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}