{"id":"https://openalex.org/W3041654539","doi":"https://doi.org/10.24963/ijcai.2020/659","title":"NSGA-Net: Neural Architecture Search using Multi-Objective Genetic Algorithm (Extended Abstract)","display_name":"NSGA-Net: Neural Architecture Search using Multi-Objective Genetic Algorithm (Extended Abstract)","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3041654539","doi":"https://doi.org/10.24963/ijcai.2020/659","mag":"3041654539"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2020/659","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2020/659","pdf_url":"https://www.ijcai.org/proceedings/2020/0659.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2020/0659.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5027687139","display_name":"Zhichao Lu","orcid":"https://orcid.org/0000-0002-4618-3573"},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhichao Lu","raw_affiliation_strings":["MICHIGAN STATE UNIVERSITY","Michigan State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MICHIGAN STATE UNIVERSITY","institution_ids":["https://openalex.org/I87216513"]},{"raw_affiliation_string":"Michigan State University","institution_ids":["https://openalex.org/I87216513"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033455019","display_name":"Ian Whalen","orcid":null},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ian Whalen","raw_affiliation_strings":["MICHIGAN STATE UNIVERSITY","Michigan State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MICHIGAN STATE UNIVERSITY","institution_ids":["https://openalex.org/I87216513"]},{"raw_affiliation_string":"Michigan State University","institution_ids":["https://openalex.org/I87216513"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068379698","display_name":"Yashesh Dhebar","orcid":"https://orcid.org/0000-0001-8144-0566"},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yashesh Dhebar","raw_affiliation_strings":["MICHIGAN STATE UNIVERSITY","Michigan State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MICHIGAN STATE UNIVERSITY","institution_ids":["https://openalex.org/I87216513"]},{"raw_affiliation_string":"Michigan State University","institution_ids":["https://openalex.org/I87216513"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088394271","display_name":"Kalyanmoy Deb","orcid":"https://orcid.org/0000-0001-7402-9939"},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kalyanmoy Deb","raw_affiliation_strings":["MICHIGAN STATE UNIVERSITY","Michigan State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MICHIGAN STATE UNIVERSITY","institution_ids":["https://openalex.org/I87216513"]},{"raw_affiliation_string":"Michigan State University","institution_ids":["https://openalex.org/I87216513"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034853476","display_name":"Erik D. Goodman","orcid":"https://orcid.org/0000-0002-2419-0692"},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Erik Goodman","raw_affiliation_strings":["MICHIGAN STATE UNIVERSITY","Michigan State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MICHIGAN STATE UNIVERSITY","institution_ids":["https://openalex.org/I87216513"]},{"raw_affiliation_string":"Michigan State University","institution_ids":["https://openalex.org/I87216513"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004837138","display_name":"Wolfgang Banzhaf","orcid":"https://orcid.org/0000-0002-6382-3245"},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wolfgang Banzhaf","raw_affiliation_strings":["MICHIGAN STATE UNIVERSITY","Michigan State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MICHIGAN STATE UNIVERSITY","institution_ids":["https://openalex.org/I87216513"]},{"raw_affiliation_string":"Michigan State University","institution_ids":["https://openalex.org/I87216513"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031717929","display_name":"Vishnu Naresh Boddeti","orcid":"https://orcid.org/0000-0002-8918-9385"},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vishnu Naresh Boddeti","raw_affiliation_strings":["MICHIGAN STATE UNIVERSITY","Michigan State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MICHIGAN STATE UNIVERSITY","institution_ids":["https://openalex.org/I87216513"]},{"raw_affiliation_string":"Michigan State University","institution_ids":["https://openalex.org/I87216513"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I87216513"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4750","last_page":"4754"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998000264167786,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9998000264167786,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9994999766349792,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7964913249015808},{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.6663727164268494},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6315723061561584},{"id":"https://openalex.org/keywords/crossover","display_name":"Crossover","score":0.5461469888687134},{"id":"https://openalex.org/keywords/flexibility","display_name":"Flexibility (engineering)","score":0.5335566997528076},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.5260174870491028},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.517941415309906},{"id":"https://openalex.org/keywords/evolutionary-algorithm","display_name":"Evolutionary algorithm","score":0.5147050023078918},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5086613297462463},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.5024333000183105},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4926658272743225},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.47573256492614746},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.42672935128211975},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4169897735118866},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.41694873571395874},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0997212827205658}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7964913249015808},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.6663727164268494},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6315723061561584},{"id":"https://openalex.org/C122507166","wikidata":"https://www.wikidata.org/wiki/Q628906","display_name":"Crossover","level":2,"score":0.5461469888687134},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.5335566997528076},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.5260174870491028},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.517941415309906},{"id":"https://openalex.org/C159149176","wikidata":"https://www.wikidata.org/wiki/Q14489129","display_name":"Evolutionary algorithm","level":2,"score":0.5147050023078918},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5086613297462463},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.5024333000183105},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4926658272743225},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.47573256492614746},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.42672935128211975},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4169897735118866},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.41694873571395874},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0997212827205658},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","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},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","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/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2020/659","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2020/659","pdf_url":"https://www.ijcai.org/proceedings/2020/0659.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2020/659","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2020/659","pdf_url":"https://www.ijcai.org/proceedings/2020/0659.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.550000011920929}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3041654539.pdf","grobid_xml":"https://content.openalex.org/works/W3041654539.grobid-xml"},"referenced_works_count":21,"referenced_works":["https://openalex.org/W1497256448","https://openalex.org/W1686810756","https://openalex.org/W1836465849","https://openalex.org/W2097117768","https://openalex.org/W2101008160","https://openalex.org/W2108772909","https://openalex.org/W2194775991","https://openalex.org/W2468462628","https://openalex.org/W2553303224","https://openalex.org/W2939863610","https://openalex.org/W2949264490","https://openalex.org/W2951104886","https://openalex.org/W2962746461","https://openalex.org/W2963125010","https://openalex.org/W2963163009","https://openalex.org/W2963446712","https://openalex.org/W2963551763","https://openalex.org/W2964081807","https://openalex.org/W2965658867","https://openalex.org/W3118608800","https://openalex.org/W4297917482"],"related_works":["https://openalex.org/W3204184292","https://openalex.org/W3176564347","https://openalex.org/W1985458517","https://openalex.org/W2347477706","https://openalex.org/W2355833770","https://openalex.org/W1606499289","https://openalex.org/W1985939653","https://openalex.org/W2014162767","https://openalex.org/W2911578165","https://openalex.org/W2626282817"],"abstract_inverted_index":{"Convolutional":[0],"neural":[1,30,64,110],"networks":[2],"(CNNs)":[3],"are":[4,20,131],"the":[5,37,41,99,105,113,169],"backbones":[6],"of":[7,39,62,90,108,115,121,128],"deep":[8],"learning":[9],"paradigms":[10],"for":[11,157],"numerous":[12],"vision":[13],"tasks.":[14],"Early":[15],"advancements":[16],"in":[17,67,104,112,134,168],"CNN":[18],"architectures":[19,66,111,129,143],"primarily":[21],"driven":[22],"by":[23],"human":[24],"expertise":[25],"and":[26,45,88,92,133,140],"elaborate":[27],"design.":[28],"Recently,":[29],"architecture":[31,155],"search":[32,56],"(NAS)":[33],"was":[34],"proposed":[35],"with":[36],"aim":[38],"automating":[40],"network":[42,65],"design":[43,127],"process":[44],"generating":[46],"task-dependent":[47],"architectures.":[48],"This":[49],"paper":[50],"introduces":[51],"NSGA-Net":[52],"--":[53],"an":[54,83,94,125],"evolutionary":[55],"algorithm":[57],"that":[58,75,97,130],"explores":[59],"a":[60,71,116],"space":[61],"potential":[63],"three":[68],"steps,":[69],"namely,":[70],"population":[72],"initialization":[73],"step":[74,85,96],"is":[76],"based":[77],"on":[78,144],"prior-knowledge":[79],"from":[80,151,165],"hand-crafted":[81],"architectures,":[82,91],"exploration":[84],"comprising":[86],"crossover":[87],"mutation":[89],"finally":[93],"exploitation":[95],"utilizes":[98],"hidden":[100],"useful":[101],"knowledge":[102],"stored":[103],"entire":[106],"history":[107],"evaluated":[109],"form":[114],"Bayesian":[117],"Network.":[118],"The":[119,148],"integration":[120],"these":[122],"components":[123],"allows":[124],"efficient":[126],"competitive":[132],"many":[135],"cases":[136],"outperform":[137],"both":[138],"manually":[139],"automatically":[141],"designed":[142],"CIFAR-10":[145],"classification":[146],"task.":[147],"flexibility":[149],"provided":[150],"simultaneously":[152],"obtaining":[153],"multiple":[154],"choices":[156],"different":[158],"compute":[159],"requirements":[160],"further":[161],"differentiates":[162],"our":[163],"approach":[164],"other":[166],"methods":[167],"literature.":[170]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
