{"id":"https://openalex.org/W4311300573","doi":"https://doi.org/10.1145/3565387.3565403","title":"Finding Key Training Data by Calculating Influence Score","display_name":"Finding Key Training Data by Calculating Influence Score","publication_year":2022,"publication_date":"2022-10-21","ids":{"openalex":"https://openalex.org/W4311300573","doi":"https://doi.org/10.1145/3565387.3565403"},"language":"en","primary_location":{"id":"doi:10.1145/3565387.3565403","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3565387.3565403","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 6th International Conference on Computer Science and Application Engineering","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/A5101622579","display_name":"Jiahao Xu","orcid":"https://orcid.org/0009-0006-8410-2371"},"institutions":[{"id":"https://openalex.org/I134687103","display_name":"Nanjing Tech University","ror":"https://ror.org/03sd35x91","country_code":"CN","type":"education","lineage":["https://openalex.org/I134687103"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiahao Xu","raw_affiliation_strings":["Nanjing Tech University, China"],"affiliations":[{"raw_affiliation_string":"Nanjing Tech University, China","institution_ids":["https://openalex.org/I134687103"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100403515","display_name":"Fan Zhang","orcid":"https://orcid.org/0000-0002-8735-2812"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fan Zhang","raw_affiliation_strings":["IBM Massachusetts Lab, USA"],"affiliations":[{"raw_affiliation_string":"IBM Massachusetts Lab, USA","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003909640","display_name":"Samee U. Khan","orcid":"https://orcid.org/0000-0001-5640-4942"},"institutions":[{"id":"https://openalex.org/I99041443","display_name":"Mississippi State University","ror":"https://ror.org/0432jq872","country_code":"US","type":"education","lineage":["https://openalex.org/I4210141039","https://openalex.org/I99041443"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Samee U. Khan","raw_affiliation_strings":["Mississippi State University, USA"],"affiliations":[{"raw_affiliation_string":"Mississippi State University, USA","institution_ids":["https://openalex.org/I99041443"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101622579"],"corresponding_institution_ids":["https://openalex.org/I134687103"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.11522764,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9987999796867371,"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"}},"topics":[{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9987999796867371,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9962999820709229,"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/T10320","display_name":"Neural Networks and Applications","score":0.9921000003814697,"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/overfitting","display_name":"Overfitting","score":0.8824390769004822},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.8494815826416016},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7651636600494385},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.7535281181335449},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.7070640325546265},{"id":"https://openalex.org/keywords/sorting","display_name":"Sorting","score":0.6217250823974609},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.5684565305709839},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.5380688309669495},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5215301513671875},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4828627407550812},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4576927125453949},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4286488890647888},{"id":"https://openalex.org/keywords/volume","display_name":"Volume (thermodynamics)","score":0.41724807024002075},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.4148483872413635},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.18960151076316833},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.13586220145225525}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.8824390769004822},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.8494815826416016},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7651636600494385},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.7535281181335449},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.7070640325546265},{"id":"https://openalex.org/C111696304","wikidata":"https://www.wikidata.org/wiki/Q2303697","display_name":"Sorting","level":2,"score":0.6217250823974609},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.5684565305709839},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.5380688309669495},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5215301513671875},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4828627407550812},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4576927125453949},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4286488890647888},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.41724807024002075},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.4148483872413635},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.18960151076316833},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.13586220145225525},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","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},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3565387.3565403","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3565387.3565403","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 6th International Conference on Computer Science and Application Engineering","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":13,"referenced_works":["https://openalex.org/W1989898472","https://openalex.org/W2597603852","https://openalex.org/W2889331981","https://openalex.org/W2889374687","https://openalex.org/W2903996579","https://openalex.org/W3101656801","https://openalex.org/W3107569919","https://openalex.org/W3136524425","https://openalex.org/W3177900337","https://openalex.org/W4286277022","https://openalex.org/W4287077733","https://openalex.org/W6600009415","https://openalex.org/W6600553734"],"related_works":["https://openalex.org/W4362597605","https://openalex.org/W1574414179","https://openalex.org/W2905433371","https://openalex.org/W4297676672","https://openalex.org/W1585770001","https://openalex.org/W2075873371","https://openalex.org/W4245210885","https://openalex.org/W84383711","https://openalex.org/W4242351093","https://openalex.org/W2066625485"],"abstract_inverted_index":{"Due":[0],"to":[1,19,92],"the":[2,49,69,72,78,83,86,95,106,113,118],"complexity":[3],"and":[4,9,23,44,46,80,85,128],"opacity":[5],"of":[6,60,71,82,108,117],"decision":[7],"models":[8],"increasing":[10],"data":[11,21,42,51,73,88],"volume":[12,22],"requirements,":[13],"this":[14,32,54],"makes":[15],"it":[16],"more":[17,90],"attractive":[18],"reduce":[20],"improve":[24],"model":[25,96],"interpretability":[26],"by":[27,53,110],"selecting":[28],"key":[29,50,87],"data.":[30,62,119],"In":[31,63],"paper,":[33],"we":[34,65],"propose":[35],"an":[36,57],"influence":[37],"function-based":[38],"method":[39,55,102,125],"InfSort":[40],"for":[41,112],"sorting":[43],"pruning,":[45],"demonstrate":[47],"that":[48,68,104,123],"selected":[52],"outperforms":[56],"equal":[58],"number":[59],"other":[61],"addition,":[64],"also":[66,99],"found":[67],"importance":[70],"is":[74,89,126],"positively":[75],"correlated":[76],"with":[77],"speed":[79],"stability":[81],"loss,":[84],"conducive":[91],"speeding":[93],"up":[94],"convergence.":[97],"We":[98],"developed":[100],"a":[101],"CGT":[103],"prevents":[105],"risk":[107],"overfitting":[109],"controlling":[111],"worst":[114],"case":[115],"distribution":[116],"Experimental":[120],"results":[121],"show":[122],"our":[124],"effective":[127],"efficient":[129],"in":[130],"emotion":[131],"recognition":[132],"tasks.":[133]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
