{"id":"https://openalex.org/W4229031345","doi":"https://doi.org/10.1145/3477314.3507059","title":"Repairing misclassifications in neural networks using limited data","display_name":"Repairing misclassifications in neural networks using limited data","publication_year":2022,"publication_date":"2022-04-25","ids":{"openalex":"https://openalex.org/W4229031345","doi":"https://doi.org/10.1145/3477314.3507059"},"language":"en","primary_location":{"id":"doi:10.1145/3477314.3507059","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3477314.3507059","pdf_url":null,"source":{"id":"https://openalex.org/S4363608665","display_name":"Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing","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/A5013371520","display_name":"Patrick Henriksen","orcid":null},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Patrick Henriksen","raw_affiliation_strings":["Imperial College London, London, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Imperial College London, London, United Kingdom","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043590673","display_name":"Francesco Leofante","orcid":"https://orcid.org/0000-0001-8245-9429"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Francesco Leofante","raw_affiliation_strings":["Imperial College London, London, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Imperial College London, London, United Kingdom","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015045050","display_name":"Alessio Lomuscio","orcid":"https://orcid.org/0000-0003-3420-723X"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Alessio Lomuscio","raw_affiliation_strings":["Imperial College London, London, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Imperial College London, London, United Kingdom","institution_ids":["https://openalex.org/I47508984"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5013371520"],"corresponding_institution_ids":["https://openalex.org/I47508984"],"apc_list":null,"apc_paid":null,"fwci":1.9931,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.88387746,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1031","last_page":"1038"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9998999834060669,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","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/T10036","display_name":"Advanced Neural Network Applications","score":0.9948999881744385,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9911999702453613,"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/soundness","display_name":"Soundness","score":0.8090279698371887},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7909528017044067},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.7903797626495361},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6295946836471558},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.506227433681488},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4982171058654785},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4196990728378296},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4120393395423889},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3503321707248688},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32996100187301636}],"concepts":[{"id":"https://openalex.org/C39920170","wikidata":"https://www.wikidata.org/wiki/Q693083","display_name":"Soundness","level":2,"score":0.8090279698371887},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7909528017044067},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7903797626495361},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6295946836471558},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.506227433681488},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4982171058654785},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4196990728378296},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4120393395423889},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3503321707248688},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32996100187301636},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3477314.3507059","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3477314.3507059","pdf_url":null,"source":{"id":"https://openalex.org/S4363608665","display_name":"Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing","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":7,"referenced_works":["https://openalex.org/W2241862190","https://openalex.org/W2346933546","https://openalex.org/W2560674852","https://openalex.org/W2608239929","https://openalex.org/W2972713160","https://openalex.org/W3012981624","https://openalex.org/W3037629243"],"related_works":["https://openalex.org/W1511249877","https://openalex.org/W2466303427","https://openalex.org/W1578828174","https://openalex.org/W2786391746","https://openalex.org/W3132346564","https://openalex.org/W2991483587","https://openalex.org/W2914559142","https://openalex.org/W4226059458","https://openalex.org/W4381430104","https://openalex.org/W2995102745"],"abstract_inverted_index":{"We":[0,34,55,82],"present":[1,35],"a":[2,10,17,36,57],"novel":[3],"and":[4,44,53,87],"computationally":[5],"efficient":[6],"method":[7,26],"for":[8,39,110],"repairing":[9,40],"feed-forward":[11],"neural":[12,42,94],"network":[13,43,76],"with":[14],"respect":[15],"to":[16,30,64,92,102,106],"finite":[18],"set":[19],"of":[20,51],"inputs":[21],"that":[22,60,69],"are":[23,71],"misclassified.":[24],"The":[25],"assumes":[27],"no":[28],"access":[29],"the":[31,41,65],"training":[32],"set.":[33],"formal":[37],"characterisation":[38],"study":[45],"its":[46],"resulting":[47],"properties":[48],"in":[49],"terms":[50],"soundness":[52],"minimality.":[54],"introduce":[56,83],"gradient-based":[58],"algorithm":[59],"performs":[61],"localised":[62],"modifications":[63],"network's":[66],"weights":[67],"such":[68],"misclassifications":[70],"repaired":[72],"while":[73,96],"marginally":[74],"affecting":[75],"accuracy":[77,98],"on":[78],"correctly":[79],"classified":[80],"inputs.":[81],"an":[84],"implementation,":[85],"I-REPAIR,":[86],"show":[88],"it":[89],"is":[90],"able":[91],"repair":[93],"networks":[95],"reducing":[97],"drops":[99],"by":[100],"up":[101],"90%":[103],"when":[104],"compared":[105],"other":[107],"state-of-the-art":[108],"approaches":[109],"repair.":[111]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":5}],"updated_date":"2026-03-13T16:22:10.518609","created_date":"2025-10-10T00:00:00"}