{"id":"https://openalex.org/W2734593927","doi":"https://doi.org/10.1145/3067695.3076091","title":"Late-acceptance and step-counting hill-climbing GP for anomaly detection","display_name":"Late-acceptance and step-counting hill-climbing GP for anomaly detection","publication_year":2017,"publication_date":"2017-07-11","ids":{"openalex":"https://openalex.org/W2734593927","doi":"https://doi.org/10.1145/3067695.3076091","mag":"2734593927"},"language":"en","primary_location":{"id":"doi:10.1145/3067695.3076091","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3067695.3076091","pdf_url":null,"source":{"id":"https://openalex.org/S4363608771","display_name":"Proceedings of the Genetic and Evolutionary Computation Conference Companion","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 Genetic and Evolutionary Computation Conference Companion","raw_type":"proceedings-article"},"type":"conference-paper","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/A5082857079","display_name":"Van Loi Cao","orcid":"https://orcid.org/0000-0002-3637-9230"},"institutions":[{"id":"https://openalex.org/I100930933","display_name":"University College Dublin","ror":"https://ror.org/05m7pjf47","country_code":"IE","type":"education","lineage":["https://openalex.org/I100930933"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Van Loi Cao","raw_affiliation_strings":["University College Dublin, Dublin, Ireland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University College Dublin, Dublin, Ireland","institution_ids":["https://openalex.org/I100930933"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085107807","display_name":"Miguel Nicolau","orcid":"https://orcid.org/0000-0002-1981-1300"},"institutions":[{"id":"https://openalex.org/I100930933","display_name":"University College Dublin","ror":"https://ror.org/05m7pjf47","country_code":"IE","type":"education","lineage":["https://openalex.org/I100930933"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Miguel Nicolau","raw_affiliation_strings":["University College Dublin, Dublin, Ireland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University College Dublin, Dublin, Ireland","institution_ids":["https://openalex.org/I100930933"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067381332","display_name":"James McDermott","orcid":"https://orcid.org/0000-0002-1402-6995"},"institutions":[{"id":"https://openalex.org/I100930933","display_name":"University College Dublin","ror":"https://ror.org/05m7pjf47","country_code":"IE","type":"education","lineage":["https://openalex.org/I100930933"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"James McDermott","raw_affiliation_strings":["University College Dublin, Dublin, Ireland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University College Dublin, Dublin, Ireland","institution_ids":["https://openalex.org/I100930933"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I100930933"],"apc_list":null,"apc_paid":null,"fwci":0.2768,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.53011195,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"221","last_page":"222"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9991000294685364,"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/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9991000294685364,"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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9961000084877014,"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":0.987500011920929,"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/support-vector-machine","display_name":"Support vector machine","score":0.772091269493103},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7498360872268677},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.6526293754577637},{"id":"https://openalex.org/keywords/hill-climbing","display_name":"Hill climbing","score":0.6356598734855652},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.632940411567688},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.627235472202301},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5747516751289368},{"id":"https://openalex.org/keywords/climbing","display_name":"Climbing","score":0.5146823525428772},{"id":"https://openalex.org/keywords/kernel-density-estimation","display_name":"Kernel density estimation","score":0.5055482387542725},{"id":"https://openalex.org/keywords/genetic-programming","display_name":"Genetic programming","score":0.465422123670578},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4520846903324127},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.44551846385002136},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33850109577178955},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11747696995735168},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.06601577997207642}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.772091269493103},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7498360872268677},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6526293754577637},{"id":"https://openalex.org/C135450995","wikidata":"https://www.wikidata.org/wiki/Q820272","display_name":"Hill climbing","level":2,"score":0.6356598734855652},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.632940411567688},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.627235472202301},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5747516751289368},{"id":"https://openalex.org/C95038775","wikidata":"https://www.wikidata.org/wiki/Q22857","display_name":"Climbing","level":2,"score":0.5146823525428772},{"id":"https://openalex.org/C71134354","wikidata":"https://www.wikidata.org/wiki/Q458825","display_name":"Kernel density estimation","level":3,"score":0.5055482387542725},{"id":"https://openalex.org/C110332635","wikidata":"https://www.wikidata.org/wiki/Q629498","display_name":"Genetic programming","level":2,"score":0.465422123670578},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4520846903324127},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.44551846385002136},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33850109577178955},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11747696995735168},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06601577997207642},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3067695.3076091","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3067695.3076091","pdf_url":null,"source":{"id":"https://openalex.org/S4363608771","display_name":"Proceedings of the Genetic and Evolutionary Computation Conference Companion","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 Genetic and Evolutionary Computation Conference Companion","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W1534539971","https://openalex.org/W2108910404","https://openalex.org/W2332118307","https://openalex.org/W2338990760","https://openalex.org/W2340896621","https://openalex.org/W2345951342","https://openalex.org/W2516866958"],"related_works":["https://openalex.org/W643038845","https://openalex.org/W2143761673","https://openalex.org/W2521924929","https://openalex.org/W4317738234","https://openalex.org/W2030861990","https://openalex.org/W2060963430","https://openalex.org/W60142908","https://openalex.org/W2406935090","https://openalex.org/W4296626987","https://openalex.org/W2020542318"],"abstract_inverted_index":{"One-Class":[0],"Classification":[1],"(OCC)":[2],"for":[3,9],"anomaly":[4,10],"detection":[5,11],"is":[6,77,146],"a":[7,14,84],"method":[8],"that":[12,131,150],"constructs":[13],"classifier":[15],"from":[16,58,83],"only":[17],"normal":[18],"examples.":[19],"Classifier":[20],"systems":[21],"such":[22],"as":[23,107],"Kernel":[24],"Density":[25],"Estimation":[26],"(KDE)":[27],"and":[28,69,80,101,122,140,153],"Support":[29],"Vector":[30],"Machine":[31],"(SVM)":[32],"typically":[33],"do":[34],"well":[35],"at":[36],"this":[37,91],"task,":[38],"but":[39],"can":[40],"be":[41],"slow":[42],"when":[43],"classifying":[44],"new":[45],"instances.":[46],"Previous":[47],"work":[48],"has":[49],"used":[50],"Genetic":[51],"Programming":[52],"(GP)":[53],"to":[54,86,118,126],"learn":[55],"the":[56,75,96,132,158],"density":[57],"KDE,":[59],"with":[60,115,137,157],"results":[61,129],"often":[62,141],"out-performing":[63],"those":[64],"of":[65,151,160],"one-class":[66],"SVM":[67],"(OCSVM)":[68],"KDE":[70],"based":[71],"OCC":[72],"(OCKDE).":[73],"However,":[74],"search":[76],"computationally":[78],"expensive,":[79],"it":[81],"suffers":[82],"need":[85],"tune":[87],"many":[88],"parameters.":[89],"In":[90],"paper,":[92],"we":[93],"will":[94],"introduce":[95],"Late":[97],"Acceptance":[98],"Hill-Climbing":[99,104],"(LAHC)":[100],"Step":[102],"Counting":[103],"(SCHC)":[105],"algorithms":[106],"GP":[108],"alternatives.":[109],"These":[110],"are":[111,135],"simple":[112],"hill-climbing":[113],"algorithms,":[114],"specific":[116],"methods":[117],"avoid":[119],"local":[120],"optima,":[121],"far":[123],"less":[124,148],"parameters":[125],"tune.":[127],"The":[128],"demonstrate":[130],"proposed":[133],"models":[134],"competitive":[136],"standard":[138],"GP,":[139],"out-perform":[142],"OCSVM.":[143],"Their":[144],"query-time":[145],"much":[147],"than":[149],"OCSVM,":[152],"does":[154],"not":[155],"scale":[156],"size":[159],"training":[161],"data.":[162]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}