{"id":"https://openalex.org/W1987817443","doi":"https://doi.org/10.1145/2330163.2330204","title":"A memory efficient and continuous-valued compact EDA for large scale problems","display_name":"A memory efficient and continuous-valued compact EDA for large scale problems","publication_year":2012,"publication_date":"2012-07-07","ids":{"openalex":"https://openalex.org/W1987817443","doi":"https://doi.org/10.1145/2330163.2330204","mag":"1987817443"},"language":"en","primary_location":{"id":"doi:10.1145/2330163.2330204","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2330163.2330204","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 14th annual conference on Genetic and evolutionary computation","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/A5060585489","display_name":"Sergio Rojas\u2013Galeano","orcid":"https://orcid.org/0000-0002-5062-2487"},"institutions":[{"id":"https://openalex.org/I332011152","display_name":"Universidad Distrital Francisco Jos\u00e9 de Caldas","ror":"https://ror.org/02jsxd428","country_code":"CO","type":"education","lineage":["https://openalex.org/I332011152"]}],"countries":["CO"],"is_corresponding":false,"raw_author_name":"Sergio Rojas-Galeano","raw_affiliation_strings":["District University of Bogota, Bogota, Colombia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"District University of Bogota, Bogota, Colombia","institution_ids":["https://openalex.org/I332011152"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111429094","display_name":"N\u00e9stor Rodr\u00edguez","orcid":"https://orcid.org/0009-0000-0208-2212"},"institutions":[{"id":"https://openalex.org/I332011152","display_name":"Universidad Distrital Francisco Jos\u00e9 de Caldas","ror":"https://ror.org/02jsxd428","country_code":"CO","type":"education","lineage":["https://openalex.org/I332011152"]}],"countries":["CO"],"is_corresponding":false,"raw_author_name":"Nestor Rodriguez","raw_affiliation_strings":["District University of Bogota, Bogota, Colombia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"District University of Bogota, Bogota, Colombia","institution_ids":["https://openalex.org/I332011152"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I332011152"],"apc_list":null,"apc_paid":null,"fwci":0.7805,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.68138584,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"281","last_page":"288"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9932000041007996,"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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9932000041007996,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9851999878883362,"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/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9800000190734863,"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/coding","display_name":"Coding (social sciences)","score":0.6426250338554382},{"id":"https://openalex.org/keywords/estimation-of-distribution-algorithm","display_name":"Estimation of distribution algorithm","score":0.6420010328292847},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.5799810886383057},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5546410083770752},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.5141034722328186},{"id":"https://openalex.org/keywords/fitness-function","display_name":"Fitness function","score":0.4929535388946533},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4906546175479889},{"id":"https://openalex.org/keywords/binary-code","display_name":"Binary code","score":0.47526973485946655},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.45276984572410583},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.42374980449676514},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.41076481342315674},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3031266927719116},{"id":"https://openalex.org/keywords/arithmetic","display_name":"Arithmetic","score":0.27442029118537903},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.15928199887275696},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10220393538475037}],"concepts":[{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.6426250338554382},{"id":"https://openalex.org/C162500139","wikidata":"https://www.wikidata.org/wiki/Q2835887","display_name":"Estimation of distribution algorithm","level":2,"score":0.6420010328292847},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.5799810886383057},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5546410083770752},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.5141034722328186},{"id":"https://openalex.org/C176066374","wikidata":"https://www.wikidata.org/wiki/Q629118","display_name":"Fitness function","level":3,"score":0.4929535388946533},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4906546175479889},{"id":"https://openalex.org/C63435697","wikidata":"https://www.wikidata.org/wiki/Q864135","display_name":"Binary code","level":3,"score":0.47526973485946655},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.45276984572410583},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.42374980449676514},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.41076481342315674},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3031266927719116},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.27442029118537903},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.15928199887275696},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10220393538475037},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","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:10.1145/2330163.2330204","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2330163.2330204","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 14th annual conference on Genetic and evolutionary computation","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":24,"referenced_works":["https://openalex.org/W73718217","https://openalex.org/W118172543","https://openalex.org/W1479800076","https://openalex.org/W1507225143","https://openalex.org/W1534948419","https://openalex.org/W1540706608","https://openalex.org/W1578993946","https://openalex.org/W1639032689","https://openalex.org/W1966241132","https://openalex.org/W1966497546","https://openalex.org/W1978035001","https://openalex.org/W1982812074","https://openalex.org/W2020009149","https://openalex.org/W2086140974","https://openalex.org/W2095965475","https://openalex.org/W2107951961","https://openalex.org/W2109943925","https://openalex.org/W2126759136","https://openalex.org/W2135864272","https://openalex.org/W2139015486","https://openalex.org/W2148379945","https://openalex.org/W2152828142","https://openalex.org/W2162036626","https://openalex.org/W4298056715"],"related_works":["https://openalex.org/W2106492215","https://openalex.org/W2326694407","https://openalex.org/W2082859007","https://openalex.org/W2164831575","https://openalex.org/W2378719652","https://openalex.org/W2115729582","https://openalex.org/W2094658154","https://openalex.org/W2370837632","https://openalex.org/W2353187647","https://openalex.org/W4286340544"],"abstract_inverted_index":{"This":[0,70],"paper":[1],"considers":[2],"large-scale":[3],"OneMax":[4],"and":[5,38,54,99,107],"RoyalRoad":[6],"problems":[7,59],"with":[8,60],"up":[9],"to":[10,50,75],"107":[11],"binary":[12],"variables":[13],"within":[14],"a":[15,44,79],"compact":[16,26,103],"Estimation":[17],"of":[18,57,65,90],"Distribution":[19],"Algorithms":[20],"(EDA)":[21],"framework.":[22],"Building":[23],"upon":[24],"the":[25,30,39,73,91],"Genetic":[27],"Algorithm":[28],"(cGA),":[29],"continuous":[31],"domain":[32],"Population-Based":[33],"Incremental":[34],"Learning":[35],"algorithm":[36,74],"(PBILc)":[37],"arithmetic-coding":[40,92],"EDA,":[41],"we":[42],"define":[43],"novel":[45],"method":[46],"that":[47],"is":[48],"able":[49],"compactly":[51],"solve":[52],"regular":[53],"noisy":[55],"versions":[56],"these":[58],"minimal":[61],"memory":[62],"requirements,":[63],"regardless":[64],"problem":[66],"or":[67],"population":[68],"size.":[69],"feature":[71],"allows":[72],"be":[76],"run":[77],"in":[78],"conventional":[80],"desktop":[81],"machine.":[82],"Issues":[83],"regarding":[84],"probability":[85],"model":[86],"sampling,":[87],"arbitrary":[88],"precision":[89],"decompressing":[93],"scheme,":[94],"incremental":[95],"fitness":[96],"function":[97],"evaluation":[98],"updating":[100],"rules":[101],"for":[102],"learning,":[104],"are":[105],"presented":[106],"discussed.":[108]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2015,"cited_by_count":2},{"year":2013,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}