{"id":"https://openalex.org/W4388819972","doi":"https://doi.org/10.1109/tbdata.2023.3334648","title":"FATS: Feature Distribution Analysis-Based Test Selection for Deep Learning Enhancement","display_name":"FATS: Feature Distribution Analysis-Based Test Selection for Deep Learning Enhancement","publication_year":2023,"publication_date":"2023-11-20","ids":{"openalex":"https://openalex.org/W4388819972","doi":"https://doi.org/10.1109/tbdata.2023.3334648"},"language":"en","primary_location":{"id":"doi:10.1109/tbdata.2023.3334648","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/tbdata.2023.3334648","pdf_url":null,"source":{"id":"https://openalex.org/S2491400915","display_name":"IEEE Transactions on Big Data","issn_l":"2332-7790","issn":["2332-7790","2372-2096"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Big Data","raw_type":"journal-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/A5103102291","display_name":"Li Li","orcid":"https://orcid.org/0000-0003-1810-1216"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Li Li","raw_affiliation_strings":["College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China","institution_ids":["https://openalex.org/I9842412"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002015838","display_name":"Chuanqi Tao","orcid":"https://orcid.org/0000-0002-0698-7307"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]},{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chuanqi Tao","raw_affiliation_strings":["College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China","Ministry Key Laboratory for Safety-Critical Software Development and Verification, Nanjing University of Aeronautics and Astronautics, Nanjing, China","State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China","institution_ids":["https://openalex.org/I9842412"]},{"raw_affiliation_string":"Ministry Key Laboratory for Safety-Critical Software Development and Verification, Nanjing University of Aeronautics and Astronautics, Nanjing, China","institution_ids":["https://openalex.org/I9842412"]},{"raw_affiliation_string":"State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017044047","display_name":"Hongjing Guo","orcid":"https://orcid.org/0000-0001-5286-874X"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongjing Guo","raw_affiliation_strings":["College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China","institution_ids":["https://openalex.org/I9842412"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005439960","display_name":"Jingxuan Zhang","orcid":"https://orcid.org/0000-0002-8437-6640"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingxuan Zhang","raw_affiliation_strings":["College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China","institution_ids":["https://openalex.org/I9842412"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006966486","display_name":"Xiaobing Sun","orcid":"https://orcid.org/0000-0001-5165-5080"},"institutions":[{"id":"https://openalex.org/I78978612","display_name":"Yangzhou University","ror":"https://ror.org/03tqb8s11","country_code":"CN","type":"education","lineage":["https://openalex.org/I78978612"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaobing Sun","raw_affiliation_strings":["School of Information Engineering, Yangzhou University, Jiangsu, China"],"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Yangzhou University, Jiangsu, China","institution_ids":["https://openalex.org/I78978612"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5103102291"],"corresponding_institution_ids":["https://openalex.org/I9842412"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.15516413,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"10","issue":"2","first_page":"132","last_page":"145"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine 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/T11689","display_name":"Adversarial Robustness in Machine 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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9997000098228455,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9991999864578247,"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/computer-science","display_name":"Computer science","score":0.7387533783912659},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.682218611240387},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6781244277954102},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.6593623161315918},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.6051247119903564},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.5819677114486694},{"id":"https://openalex.org/keywords/test-data","display_name":"Test data","score":0.5218366980552673},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4939118027687073},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4914344549179077},{"id":"https://openalex.org/keywords/test","display_name":"Test (biology)","score":0.44577503204345703},{"id":"https://openalex.org/keywords/model-selection","display_name":"Model selection","score":0.423663854598999},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.41419684886932373},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3281874656677246}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7387533783912659},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.682218611240387},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6781244277954102},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.6593623161315918},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6051247119903564},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.5819677114486694},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.5218366980552673},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4939118027687073},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4914344549179077},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.44577503204345703},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.423663854598999},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.41419684886932373},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3281874656677246},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tbdata.2023.3334648","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/tbdata.2023.3334648","pdf_url":null,"source":{"id":"https://openalex.org/S2491400915","display_name":"IEEE Transactions on Big Data","issn_l":"2332-7790","issn":["2332-7790","2372-2096"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Big Data","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1533970194","display_name":null,"funder_award_id":"61402229","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1553128828","display_name":null,"funder_award_id":"xcxjh20221613","funder_id":"https://openalex.org/F4320322438","funder_display_name":"Nanjing University of Aeronautics and Astronautics"},{"id":"https://openalex.org/G7844191210","display_name":null,"funder_award_id":"61602267","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322438","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W1857789879","https://openalex.org/W1934184906","https://openalex.org/W1945616565","https://openalex.org/W2065010255","https://openalex.org/W2073849744","https://openalex.org/W2108862644","https://openalex.org/W2112796928","https://openalex.org/W2139380585","https://openalex.org/W2149427297","https://openalex.org/W2180612164","https://openalex.org/W2194775991","https://openalex.org/W2295598076","https://openalex.org/W2335728318","https://openalex.org/W2342840547","https://openalex.org/W2419180118","https://openalex.org/W2471222571","https://openalex.org/W2533523411","https://openalex.org/W2565516711","https://openalex.org/W2594110573","https://openalex.org/W2601243251","https://openalex.org/W2753315806","https://openalex.org/W2786808285","https://openalex.org/W2903158431","https://openalex.org/W2948254043","https://openalex.org/W2954629067","https://openalex.org/W2956371155","https://openalex.org/W2963327228","https://openalex.org/W2963542245","https://openalex.org/W2963857521","https://openalex.org/W2964183261","https://openalex.org/W2997532515","https://openalex.org/W3041012898","https://openalex.org/W3042703469","https://openalex.org/W3105347387","https://openalex.org/W3118608800","https://openalex.org/W3120991880","https://openalex.org/W3163879210","https://openalex.org/W4210455774","https://openalex.org/W4224214784","https://openalex.org/W4284702108","https://openalex.org/W4384302806","https://openalex.org/W6640425456","https://openalex.org/W6679436768","https://openalex.org/W6704559304","https://openalex.org/W6730035438","https://openalex.org/W6747231328","https://openalex.org/W6756615331","https://openalex.org/W6787972765","https://openalex.org/W6789560879","https://openalex.org/W7008895741","https://openalex.org/W7036630600"],"related_works":["https://openalex.org/W2188500270","https://openalex.org/W2303858293","https://openalex.org/W2028462208","https://openalex.org/W2982831492","https://openalex.org/W4285337533","https://openalex.org/W2187490799","https://openalex.org/W1574942924","https://openalex.org/W3094735304","https://openalex.org/W3138055416","https://openalex.org/W3019226033"],"abstract_inverted_index":{"Deep":[0],"Learning":[1],"has":[2],"been":[3],"applied":[4],"to":[5,80,127,135,139],"many":[6],"applications":[7],"across":[8],"different":[9],"domains.":[10],"However,":[11,53],"the":[12,16,27,62,90,96,115,142,176,183,187],"distribution":[13,92,179],"shift":[14],"between":[15],"test":[17,51,55,71,84,104,118,147,166],"data":[18,21,56,91,119,122],"and":[19,120,123,157,160,181],"training":[20,121],"is":[22,57],"a":[23,75],"major":[24],"factor":[25],"impacting":[26],"quality":[28],"of":[29,64,78,117,131,144,178,191],"deep":[30],"neural":[31],"networks":[32],"(DNNs).":[33],"To":[34,67,94],"address":[35,95],"this":[36,69,98],"issue,":[37,97],"existing":[38,83],"research":[39],"mainly":[40],"focuses":[41],"on":[42,89,154],"enhancing":[43],"DNN":[44,65,158,195],"models":[45],"by":[46],"retraining":[47],"them":[48],"using":[49],"labeled":[50],"data.":[52],"labeling":[54],"costly,":[58],"which":[59],"seriously":[60],"reduces":[61],"efficiency":[63],"testing.":[66],"solve":[68,136],"problem,":[70],"selection":[72,85,105,167],"strategically":[73],"selected":[74],"small":[76],"set":[77],"tests":[79],"label.":[81],"Unfortunately,":[82],"methods":[86,185],"seldom":[87],"focus":[88],"shift.":[93],"paper":[99],"proposes":[100],"an":[101,151],"approach":[102],"for":[103,146,194],"named":[106],"Feature":[107],"Distribution":[108],"Analysis-Based":[109],"Test":[110],"Selection":[111],"(FATS).":[112],"FATS":[113,163,173],"analyzes":[114],"distributions":[116],"then":[124,161],"adopts":[125],"learning":[126,134],"rank":[128],"(a":[129],"kind":[130],"supervised":[132],"machine":[133],"ranking":[137],"tasks)":[138],"intelligently":[140],"combine":[141],"results":[143,170],"analysis":[145],"selection.":[148],"We":[149],"conduct":[150],"empirical":[152],"study":[153],"popular":[155],"datasets":[156],"models,":[159],"compare":[162],"with":[164,186],"seven":[165],"methods.":[168],"Experiment":[169],"show":[171],"that":[172],"effectively":[174],"alleviates":[175],"impact":[177],"shifts":[180],"outperforms":[182],"compared":[184],"average":[188],"accuracy":[189],"improvement":[190],"19.6%<inline-formula><tex-math":[192],"notation=\"LaTeX\">$\\sim$</tex-math></inline-formula>69.7%":[193],"model":[196],"enhancement.":[197]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}