{"id":"https://openalex.org/W3091716143","doi":"https://doi.org/10.1109/ijcnn48605.2020.9207393","title":"Recurrent Neural Architecture Search based on Randomness-Enhanced Tabu Algorithm","display_name":"Recurrent Neural Architecture Search based on Randomness-Enhanced Tabu Algorithm","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3091716143","doi":"https://doi.org/10.1109/ijcnn48605.2020.9207393","mag":"3091716143"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn48605.2020.9207393","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn48605.2020.9207393","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Joint Conference on Neural Networks (IJCNN)","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/A5048675276","display_name":"Kai Hu","orcid":"https://orcid.org/0000-0001-7181-9935"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Kai Hu","raw_affiliation_strings":["College of Computer Science and Technology, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102022963","display_name":"Shuo Tian","orcid":"https://orcid.org/0000-0002-9010-8650"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuo Tian","raw_affiliation_strings":["College of Computer Science and Technology, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084835984","display_name":"Shasha Guo","orcid":"https://orcid.org/0000-0002-3308-9123"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shasha Guo","raw_affiliation_strings":["College of Computer Science and Technology, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100341034","display_name":"Nan Li","orcid":"https://orcid.org/0000-0002-0575-371X"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nan Li","raw_affiliation_strings":["College of Computer Science and Technology, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102883930","display_name":"Li Luo","orcid":"https://orcid.org/0000-0001-5519-3143"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Luo","raw_affiliation_strings":["College of Computer Science and Technology, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100663709","display_name":"Lei Wang","orcid":"https://orcid.org/0000-0003-0826-1152"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Wang","raw_affiliation_strings":["College of Computer Science and Technology, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5048675276"],"corresponding_institution_ids":["https://openalex.org/I170215575"],"apc_list":null,"apc_paid":null,"fwci":0.2931,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.57084762,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"32","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9994000196456909,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9987999796867371,"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":0.8190287351608276},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.7086528539657593},{"id":"https://openalex.org/keywords/perplexity","display_name":"Perplexity","score":0.6853504776954651},{"id":"https://openalex.org/keywords/tabu-search","display_name":"Tabu search","score":0.5856601595878601},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.5490369200706482},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5263777375221252},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.48223480582237244},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4642769694328308},{"id":"https://openalex.org/keywords/randomness","display_name":"Randomness","score":0.42151230573654175},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.42074185609817505},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.4197666645050049},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3925953805446625},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.22283539175987244},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.0943322479724884},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.09149965643882751},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.09040910005569458}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8190287351608276},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.7086528539657593},{"id":"https://openalex.org/C100279451","wikidata":"https://www.wikidata.org/wiki/Q372193","display_name":"Perplexity","level":3,"score":0.6853504776954651},{"id":"https://openalex.org/C123370116","wikidata":"https://www.wikidata.org/wiki/Q1424540","display_name":"Tabu search","level":2,"score":0.5856601595878601},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.5490369200706482},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5263777375221252},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.48223480582237244},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4642769694328308},{"id":"https://openalex.org/C125112378","wikidata":"https://www.wikidata.org/wiki/Q176640","display_name":"Randomness","level":2,"score":0.42151230573654175},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.42074185609817505},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.4197666645050049},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3925953805446625},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.22283539175987244},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.0943322479724884},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.09149965643882751},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.09040910005569458},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"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/ijcnn48605.2020.9207393","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn48605.2020.9207393","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.5199999809265137,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1836465849","https://openalex.org/W2084792706","https://openalex.org/W2093647425","https://openalex.org/W2107726111","https://openalex.org/W2108069432","https://openalex.org/W2108598243","https://openalex.org/W2116261113","https://openalex.org/W2117130368","https://openalex.org/W2549416390","https://openalex.org/W2553303224","https://openalex.org/W2571859396","https://openalex.org/W2605839414","https://openalex.org/W2606006859","https://openalex.org/W2743945814","https://openalex.org/W2767321762","https://openalex.org/W2810075754","https://openalex.org/W2915992092","https://openalex.org/W2949117887","https://openalex.org/W2951104886","https://openalex.org/W2951672049","https://openalex.org/W2953319219","https://openalex.org/W2962746461","https://openalex.org/W2962964385","https://openalex.org/W2963537482","https://openalex.org/W2963748792","https://openalex.org/W2963821229","https://openalex.org/W2963918968","https://openalex.org/W2963983719","https://openalex.org/W2965658867","https://openalex.org/W2986229159","https://openalex.org/W2995727387","https://openalex.org/W3083427717","https://openalex.org/W4288333794","https://openalex.org/W4294555862","https://openalex.org/W4299838440","https://openalex.org/W4300427683","https://openalex.org/W4300687381","https://openalex.org/W6637373629","https://openalex.org/W6638667902","https://openalex.org/W6720905350","https://openalex.org/W6729956949","https://openalex.org/W6736893961","https://openalex.org/W6741459021","https://openalex.org/W6742632731","https://openalex.org/W6746582238","https://openalex.org/W6748057086","https://openalex.org/W6752515464","https://openalex.org/W6764965709","https://openalex.org/W6766298268"],"related_works":["https://openalex.org/W2376415519","https://openalex.org/W4294769427","https://openalex.org/W1895908943","https://openalex.org/W4225667838","https://openalex.org/W1601381279","https://openalex.org/W4281893144","https://openalex.org/W2374747083","https://openalex.org/W4388254351","https://openalex.org/W4386270999","https://openalex.org/W2891987081"],"abstract_inverted_index":{"Deep":[0],"neural":[1,17,31,117],"networks":[2],"have":[3],"achieved":[4],"highly":[5],"competitive":[6],"performance":[7],"in":[8,11,131],"multiple":[9],"tasks":[10],"recent":[12],"years.":[13],"However,":[14],"discovering":[15],"state-of-the-art":[16],"network":[18],"architectures":[19,41],"requires":[20],"substantial":[21],"effort":[22],"from":[23],"human":[24],"experts.":[25],"To":[26],"speed":[27],"up":[28],"the":[29,44,65,69,82,89,106,115,137,142,165,168,180,184],"process,":[30],"architecture":[32,118,138,170],"search":[33,39,45,134],"(NAS)":[34],"has":[35],"been":[36],"proposed":[37],"to":[38,63,76,174],"promising":[40,189],"automatically.":[42],"Nevertheless,":[43],"process":[46],"of":[47,57,108,133,145,167],"NAS":[48],"is":[49,98,124,154],"computing-expensive":[50],"and":[51,85,136],"time-consuming,":[52],"which":[53,80,103,123,153],"even":[54],"costs":[55],"thousands":[56],"GPU":[58,121],"days.":[59],"In":[60,92,160],"this":[61],"paper,":[62],"solve":[64],"bottleneck,":[66],"we":[67,139,162],"apply":[68],"randomness-enhanced":[70],"tabu":[71],"algorithm":[72],"as":[73],"a":[74],"controller":[75],"sample":[77],"candidate":[78],"architectures,":[79],"balances":[81],"global":[83],"exploration":[84],"local":[86],"exploitation":[87],"for":[88],"architectural":[90],"solutions.":[91],"addition,":[93,161],"more":[94,126],"aggressive":[95],"weight-sharing":[96],"strategy":[97],"introduced":[99],"into":[100],"our":[101],"method,":[102],"significantly":[104],"reduces":[105],"overhead":[107],"evaluating":[109],"sampled":[110],"architectures.":[111],"Our":[112],"approach":[113],"discovers":[114],"recurrent":[116],"within":[119],"0.78":[120],"hour,":[122],"15.3x":[125],"efficient":[127],"than":[128,156],"ENAS":[129,157],"[1]":[130],"terms":[132],"time,":[135],"discovered":[140],"achieves":[141],"test":[143],"perplexity":[144],"56.1":[146],"on":[147,183],"Penn":[148],"Tree":[149],"Bank":[150],"(PTB)":[151],"dataset,":[152],"lower":[155],"by":[158,171],"2.2.":[159],"further":[163],"demonstrate":[164],"usefulness":[166],"learned":[169],"transferring":[172],"it":[173],"wiki-text-2":[175],"(WT2)":[176],"dataset":[177,186],"well.":[178],"Moreover,":[179],"extended":[181],"experiments":[182],"WT2":[185],"also":[187],"show":[188],"results.":[190]},"counts_by_year":[{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}