{"id":"https://openalex.org/W3183420147","doi":"https://doi.org/10.1109/mci.2021.3084415","title":"Self-Supervised Representation Learning for Evolutionary Neural Architecture Search","display_name":"Self-Supervised Representation Learning for Evolutionary Neural Architecture Search","publication_year":2021,"publication_date":"2021-07-21","ids":{"openalex":"https://openalex.org/W3183420147","doi":"https://doi.org/10.1109/mci.2021.3084415","mag":"3183420147"},"language":"en","primary_location":{"id":"doi:10.1109/mci.2021.3084415","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mci.2021.3084415","pdf_url":null,"source":{"id":"https://openalex.org/S104797584","display_name":"IEEE Computational Intelligence Magazine","issn_l":"1556-603X","issn":["1556-603X","1556-6048"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Computational Intelligence Magazine","raw_type":"journal-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/A5100756973","display_name":"Chen Wei","orcid":"https://orcid.org/0000-0003-0486-3084"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]},{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chen Wei","raw_affiliation_strings":["Xidian University and Xi\u2019an University of Posts & Telecommunications, China","Xidian University and Xi'an University of Posts & Telecommunications, China"],"affiliations":[{"raw_affiliation_string":"Xidian University and Xi\u2019an University of Posts & Telecommunications, China","institution_ids":["https://openalex.org/I4210136859","https://openalex.org/I149594827"]},{"raw_affiliation_string":"Xidian University and Xi'an University of Posts & Telecommunications, China","institution_ids":["https://openalex.org/I4210136859","https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010189817","display_name":"Yiping Tang","orcid":"https://orcid.org/0000-0001-7007-2630"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiping Tang","raw_affiliation_strings":["Xidian University, China"],"affiliations":[{"raw_affiliation_string":"Xidian University, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065193592","display_name":"Chuang Niu","orcid":"https://orcid.org/0000-0002-3310-7803"},"institutions":[{"id":"https://openalex.org/I165799507","display_name":"Rensselaer Polytechnic Institute","ror":"https://ror.org/01rtyzb94","country_code":"US","type":"education","lineage":["https://openalex.org/I165799507"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chuang Niu Chuang Niu","raw_affiliation_strings":["Rensselaer Polytechnic Institute"],"affiliations":[{"raw_affiliation_string":"Rensselaer Polytechnic Institute","institution_ids":["https://openalex.org/I165799507"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100931707","display_name":"Haihong Hu","orcid":"https://orcid.org/0000-0002-8396-4467"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haihong Hu","raw_affiliation_strings":["Xidian University, China"],"affiliations":[{"raw_affiliation_string":"Xidian University, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100371956","display_name":"Yue Wang","orcid":"https://orcid.org/0000-0001-6170-6451"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yue Wang","raw_affiliation_strings":["Xidian University, China"],"affiliations":[{"raw_affiliation_string":"Xidian University, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032808299","display_name":"Jimin Liang","orcid":"https://orcid.org/0000-0003-1428-5804"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jimin Liang","raw_affiliation_strings":["Xidian University, China"],"affiliations":[{"raw_affiliation_string":"Xidian University, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100756973"],"corresponding_institution_ids":["https://openalex.org/I149594827","https://openalex.org/I4210136859"],"apc_list":null,"apc_paid":null,"fwci":1.7292,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.86624183,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"16","issue":"3","first_page":"33","last_page":"49"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9865000247955322,"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":0.9865000247955322,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9847000241279602,"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":0.983299970626831,"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":0.7725595235824585},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7138882279396057},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6944477558135986},{"id":"https://openalex.org/keywords/time-delay-neural-network","display_name":"Time delay neural network","score":0.5387670993804932},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5085657835006714},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.4940500557422638},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.47537556290626526},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.4318050742149353},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4245932400226593},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.42001497745513916},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37345021963119507},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.11899459362030029}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7725595235824585},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7138882279396057},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6944477558135986},{"id":"https://openalex.org/C175202392","wikidata":"https://www.wikidata.org/wiki/Q2434543","display_name":"Time delay neural network","level":3,"score":0.5387670993804932},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5085657835006714},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.4940500557422638},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.47537556290626526},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.4318050742149353},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4245932400226593},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.42001497745513916},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37345021963119507},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.11899459362030029},{"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/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mci.2021.3084415","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mci.2021.3084415","pdf_url":null,"source":{"id":"https://openalex.org/S104797584","display_name":"IEEE Computational Intelligence Magazine","issn_l":"1556-603X","issn":["1556-603X","1556-6048"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Computational Intelligence Magazine","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":100,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1959608418","https://openalex.org/W2163605009","https://openalex.org/W2321533354","https://openalex.org/W2553303224","https://openalex.org/W2594529350","https://openalex.org/W2785325870","https://openalex.org/W2788853733","https://openalex.org/W2810075754","https://openalex.org/W2885311373","https://openalex.org/W2887063112","https://openalex.org/W2888429796","https://openalex.org/W2896457183","https://openalex.org/W2906943923","https://openalex.org/W2907492528","https://openalex.org/W2916118939","https://openalex.org/W2918342466","https://openalex.org/W2942259124","https://openalex.org/W2944213978","https://openalex.org/W2949264490","https://openalex.org/W2951104886","https://openalex.org/W2951245151","https://openalex.org/W2951622007","https://openalex.org/W2953308748","https://openalex.org/W2962711740","https://openalex.org/W2962746461","https://openalex.org/W2962750597","https://openalex.org/W2962847160","https://openalex.org/W2963263347","https://openalex.org/W2963341956","https://openalex.org/W2963374479","https://openalex.org/W2963821229","https://openalex.org/W2963946985","https://openalex.org/W2964081807","https://openalex.org/W2964212578","https://openalex.org/W2964294659","https://openalex.org/W2964515685","https://openalex.org/W2964544183","https://openalex.org/W2965658867","https://openalex.org/W2970971581","https://openalex.org/W2981406437","https://openalex.org/W2981748264","https://openalex.org/W2995181141","https://openalex.org/W2996409713","https://openalex.org/W2997699039","https://openalex.org/W2999270366","https://openalex.org/W3005680577","https://openalex.org/W3007549584","https://openalex.org/W3013310686","https://openalex.org/W3035267174","https://openalex.org/W3035524453","https://openalex.org/W3036224891","https://openalex.org/W3040986370","https://openalex.org/W3041166015","https://openalex.org/W3094801149","https://openalex.org/W3097891784","https://openalex.org/W3099431291","https://openalex.org/W3101164610","https://openalex.org/W3104882907","https://openalex.org/W3107453328","https://openalex.org/W3118608800","https://openalex.org/W3174412130","https://openalex.org/W4287715829","https://openalex.org/W4288024349","https://openalex.org/W4288419263","https://openalex.org/W4295312788","https://openalex.org/W4297778814","https://openalex.org/W4297782938","https://openalex.org/W4300687381","https://openalex.org/W4320005659","https://openalex.org/W6631190155","https://openalex.org/W6640963894","https://openalex.org/W6684191040","https://openalex.org/W6726497184","https://openalex.org/W6729956949","https://openalex.org/W6734593296","https://openalex.org/W6745728296","https://openalex.org/W6746582238","https://openalex.org/W6747899497","https://openalex.org/W6748057086","https://openalex.org/W6748587240","https://openalex.org/W6752515464","https://openalex.org/W6753278433","https://openalex.org/W6753701838","https://openalex.org/W6754929296","https://openalex.org/W6755207826","https://openalex.org/W6757204547","https://openalex.org/W6759402996","https://openalex.org/W6759828284","https://openalex.org/W6760045743","https://openalex.org/W6761996617","https://openalex.org/W6762003241","https://openalex.org/W6766978945","https://openalex.org/W6770196601","https://openalex.org/W6771784742","https://openalex.org/W6771859737","https://openalex.org/W6774067568","https://openalex.org/W6779715462","https://openalex.org/W6779787426","https://openalex.org/W6780506207"],"related_works":["https://openalex.org/W2081900870","https://openalex.org/W4375867731","https://openalex.org/W2183306018","https://openalex.org/W2549990292","https://openalex.org/W2345479200","https://openalex.org/W2951819827","https://openalex.org/W2849310602","https://openalex.org/W2611989081","https://openalex.org/W2419146053","https://openalex.org/W4319456675"],"abstract_inverted_index":{"Recently":[0],"proposed":[1,109,222],"neural":[2,8,17,27,38,47,65,84,102,117,125,133,149,198,231,235,239],"architecture":[3,12,28,71,93,113,161,240],"search":[4,241],"(NAS)":[5],"algorithms":[6],"adopt":[7],"predictors":[9,18,39,118,199,232],"to":[10,19,31,44,64,77,110,119,154,158,185],"accelerate":[11],"search.":[13],"The":[14,127,218],"capability":[15],"of":[16,25,57,83,90,101,116,124,146,214,220],"accurately":[20],"predict":[21],"the":[22,26,79,88,98,112,142,156,167,196,215,221,229],"performance":[23,100,205,247],"metrics":[24],"is":[29,40,60,74,224],"critical":[30],"NAS,":[32],"but":[33],"obtaining":[34],"training":[35,58,216],"datasets":[36],"for":[37],"often":[41],"time-consuming.":[42],"How":[43],"obtain":[45],"a":[46,54,61,69,121,131,152,171,178,183,234],"predictor":[48,236],"with":[49,136,207],"high":[50],"prediction":[51],"accuracy":[52],"using":[53,211],"small":[55],"amount":[56],"data":[59],"central":[62,179],"problem":[63],"predictor-based":[66],"NAS.":[67],"Here,":[68],"new":[70,172],"encoding":[72,94],"scheme":[73],"first":[75,128],"devised":[76],"calculate":[78],"graph":[80,132,143],"edit":[81,144],"distance":[82,145],"architectures,":[85],"which":[86,244],"overcomes":[87],"drawbacks":[89],"existing":[91],"vector-based":[92],"schemes.":[95],"To":[96],"enhance":[97],"predictive":[99],"predictors,":[103],"two":[104,137,147],"self-supervised":[105],"learning":[106,174],"methods":[107,223],"are":[108],"pre-train":[111],"embedding":[114],"part":[115],"generate":[120,159],"meaningful":[122,160],"representation":[123],"architectures.":[126],"method":[129,169],"designs":[130],"network-based":[134],"model":[135,157],"independent":[138],"branches":[139],"and":[140,251],"utilizes":[141,177],"different":[148],"architectures":[150],"as":[151,182],"supervision":[153],"force":[155],"representations.":[162],"Inspired":[163],"by":[164,227],"contrastive":[165,173],"learning,":[166],"second":[168],"presents":[170],"algorithm":[175],"that":[176,195],"feature":[180],"vector":[181],"proxy":[184],"contrast":[186],"positive":[187],"pairs":[188],"against":[189],"negative":[190],"pairs.":[191],"Experimental":[192],"results":[193],"illustrate":[194],"pre-trained":[197,230],"can":[200],"achieve":[201],"comparable":[202],"or":[203],"superior":[204],"compared":[206],"their":[208],"supervised":[209],"counterparts":[210],"only":[212],"half":[213],"samples.":[217],"effectiveness":[219],"further":[225],"validated":[226],"integrating":[228],"into":[233],"guided":[237],"evolutionary":[238],"(NPENAS)":[242],"algorithm,":[243],"achieves":[245],"stateof-the-art":[246],"on":[248],"NASBench-101,":[249],"NASBench-201,":[250],"DARTS":[252],"benchmarks":[253]},"counts_by_year":[{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}