{"id":"https://openalex.org/W3199113065","doi":"https://doi.org/10.1109/ijcnn52387.2021.9533297","title":"SSRNAS: Search Space Reduced One-shot NAS by a Recursive Attention-based Predictor with Cell Tensor-flow Diagram","display_name":"SSRNAS: Search Space Reduced One-shot NAS by a Recursive Attention-based Predictor with Cell Tensor-flow Diagram","publication_year":2021,"publication_date":"2021-07-18","ids":{"openalex":"https://openalex.org/W3199113065","doi":"https://doi.org/10.1109/ijcnn52387.2021.9533297","mag":"3199113065"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn52387.2021.9533297","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9533297","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 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/A5100320012","display_name":"Yue Liu","orcid":"https://orcid.org/0000-0001-5880-4923"},"institutions":[{"id":"https://openalex.org/I141962983","display_name":"Shanghai University of Engineering Science","ror":"https://ror.org/0557b9y08","country_code":"CN","type":"education","lineage":["https://openalex.org/I141962983"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yue Liu","raw_affiliation_strings":["School of Computer Engineering and Science Shanghai University,Shanghai,China","School of Computer Engineering and Science Shanghai University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Engineering and Science Shanghai University,Shanghai,China","institution_ids":["https://openalex.org/I141962983"]},{"raw_affiliation_string":"School of Computer Engineering and Science Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I141962983"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107954358","display_name":"Kai Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I141962983","display_name":"Shanghai University of Engineering Science","ror":"https://ror.org/0557b9y08","country_code":"CN","type":"education","lineage":["https://openalex.org/I141962983"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Zhu","raw_affiliation_strings":["School of Computer Engineering and Science Shanghai University,Shanghai,China","School of Computer Engineering and Science Shanghai University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Engineering and Science Shanghai University,Shanghai,China","institution_ids":["https://openalex.org/I141962983"]},{"raw_affiliation_string":"School of Computer Engineering and Science Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I141962983"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004343686","display_name":"Zitu Liu","orcid":"https://orcid.org/0000-0002-1195-688X"},"institutions":[{"id":"https://openalex.org/I141962983","display_name":"Shanghai University of Engineering Science","ror":"https://ror.org/0557b9y08","country_code":"CN","type":"education","lineage":["https://openalex.org/I141962983"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zitu Liu","raw_affiliation_strings":["School of Computer Engineering and Science Shanghai University,Shanghai,China","School of Computer Engineering and Science Shanghai University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Engineering and Science Shanghai University,Shanghai,China","institution_ids":["https://openalex.org/I141962983"]},{"raw_affiliation_string":"School of Computer Engineering and Science Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I141962983"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100320012"],"corresponding_institution_ids":["https://openalex.org/I141962983"],"apc_list":null,"apc_paid":null,"fwci":0.0961,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.39496732,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":93},"biblio":{"volume":null,"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":0.9997000098228455,"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":0.9997000098228455,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9991999864578247,"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":0.9987999796867371,"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":0.7140829563140869},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.6139612197875977},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.6002737283706665},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4917619526386261},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4548322856426239},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41952648758888245}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7140829563140869},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.6139612197875977},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.6002737283706665},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4917619526386261},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4548322856426239},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41952648758888245},{"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:10.1109/ijcnn52387.2021.9533297","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9533297","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6067408687","display_name":null,"funder_award_id":"52073169","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":69,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1522301498","https://openalex.org/W1536680647","https://openalex.org/W1985514943","https://openalex.org/W1995562189","https://openalex.org/W2157331557","https://openalex.org/W2160815625","https://openalex.org/W2525778437","https://openalex.org/W2553303224","https://openalex.org/W2743289088","https://openalex.org/W2746314669","https://openalex.org/W2748513770","https://openalex.org/W2810075754","https://openalex.org/W2810271953","https://openalex.org/W2887500939","https://openalex.org/W2888429796","https://openalex.org/W2915992092","https://openalex.org/W2951104886","https://openalex.org/W2953604046","https://openalex.org/W2955051405","https://openalex.org/W2960010704","https://openalex.org/W2962746461","https://openalex.org/W2963137684","https://openalex.org/W2963263347","https://openalex.org/W2963374479","https://openalex.org/W2963495494","https://openalex.org/W2963821229","https://openalex.org/W2964121744","https://openalex.org/W2964515685","https://openalex.org/W2965658867","https://openalex.org/W2967733054","https://openalex.org/W2968984153","https://openalex.org/W2980270353","https://openalex.org/W2987301155","https://openalex.org/W2995727387","https://openalex.org/W2999270366","https://openalex.org/W3007549584","https://openalex.org/W3034357629","https://openalex.org/W3034528892","https://openalex.org/W3034535818","https://openalex.org/W3034860472","https://openalex.org/W3035189477","https://openalex.org/W3090546708","https://openalex.org/W3095058588","https://openalex.org/W3096533519","https://openalex.org/W3101781196","https://openalex.org/W4239181501","https://openalex.org/W4300687381","https://openalex.org/W6631190155","https://openalex.org/W6683258052","https://openalex.org/W6726497184","https://openalex.org/W6727690538","https://openalex.org/W6729956949","https://openalex.org/W6743428213","https://openalex.org/W6743495212","https://openalex.org/W6746582238","https://openalex.org/W6748057086","https://openalex.org/W6752515464","https://openalex.org/W6753321367","https://openalex.org/W6753701838","https://openalex.org/W6759828284","https://openalex.org/W6760018943","https://openalex.org/W6761158446","https://openalex.org/W6771859737","https://openalex.org/W6774067568","https://openalex.org/W6775357449","https://openalex.org/W6784489866","https://openalex.org/W6786190944","https://openalex.org/W6864424756"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"One-shot":[0,79],"neural":[1],"architecture":[2],"search(NAS)":[3],"has":[4],"attracted":[5],"more":[6],"attention":[7,102],"since":[8],"it":[9,60],"can":[10],"provide":[11],"a":[12,72,96,118],"reasonable":[13],"performance":[14,108,135],"ranking":[15,23],"on":[16,32,99,170],"all":[17],"paths":[18],"in":[19,136,146],"the":[20,26,33,37,40,48,52,64,84,107,110,113,125,131,137,147,158],"super-net.":[21,38],"The":[22,143],"ability":[24],"of":[25,36,109,173,180],"one-shot":[27],"NAS":[28],"model":[29],"relies":[30],"heavily":[31],"training":[34,49,114,155],"process":[35,50],"However,":[39],"competition":[41],"among":[42],"architectures":[43,111,132,145],"for":[44,127,153],"shared":[45],"weights":[46],"during":[47,112],"and":[51,67,87,130,177],"Matthew":[53,159],"effect":[54],"caused":[55],"by":[56],"reward-based":[57],"methods":[58],"make":[59],"difficult":[61],"to":[62,90,105,156],"train":[63,88],"super-net":[65],"fairly":[66,89],"effectively.":[68],"In":[69,116],"this":[70],"paper,":[71],"novel":[73],"method":[74,167],"named":[75],"Search":[76],"Space":[77],"Reduced":[78],"NAS(SSRNAS),":[80],"which":[81],"continuously":[82],"decreases":[83],"search":[85,138,148,175],"space":[86,139,149,176],"improve":[91],"performance,":[92],"is":[93,103,122],"proposed.":[94],"Specifically,":[95],"predictor":[97],"based":[98],"graph":[100],"recursive":[101],"trained":[104],"evaluate":[106],"process.":[115],"addition,":[117],"dynamic":[119],"divided":[120],"threshold":[121],"used":[123],"as":[124],"basis":[126],"discarding":[128],"architectures,":[129],"with":[133],"poor":[134],"are":[140,150],"discarded":[141],"continuously.":[142],"remaining":[144],"uniformly":[151],"sampled":[152],"fair":[154],"avoid":[157],"effect.":[160],"Experimental":[161],"results":[162],"show":[163],"that":[164],"our":[165],"proposed":[166],"performs":[168],"well":[169],"three":[171],"datasets":[172],"NAS-Bench-201":[174],"cifar-10":[178],"dataset":[179],"DARTS":[181],"space.":[182]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}