{"id":"https://openalex.org/W3186451123","doi":"https://doi.org/10.1109/cvpr46437.2021.01489","title":"FP-NAS: Fast Probabilistic Neural Architecture Search","display_name":"FP-NAS: Fast Probabilistic Neural Architecture Search","publication_year":2021,"publication_date":"2021-06-01","ids":{"openalex":"https://openalex.org/W3186451123","doi":"https://doi.org/10.1109/cvpr46437.2021.01489","mag":"3186451123"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr46437.2021.01489","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr46437.2021.01489","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","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/A5002869474","display_name":"Zhicheng Yan","orcid":"https://orcid.org/0000-0002-6290-9848"},"institutions":[{"id":"https://openalex.org/I2252078561","display_name":"Meta (Israel)","ror":"https://ror.org/02388em19","country_code":"IL","type":"company","lineage":["https://openalex.org/I2252078561","https://openalex.org/I4210114444"]}],"countries":["IL"],"is_corresponding":true,"raw_author_name":"Zhicheng Yan","raw_affiliation_strings":["Facebook AI"],"affiliations":[{"raw_affiliation_string":"Facebook AI","institution_ids":["https://openalex.org/I2252078561"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080137972","display_name":"Xiaoliang Dai","orcid":"https://orcid.org/0000-0003-3098-2714"},"institutions":[{"id":"https://openalex.org/I2252078561","display_name":"Meta (Israel)","ror":"https://ror.org/02388em19","country_code":"IL","type":"company","lineage":["https://openalex.org/I2252078561","https://openalex.org/I4210114444"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Xiaoliang Dai","raw_affiliation_strings":["Facebook AI"],"affiliations":[{"raw_affiliation_string":"Facebook AI","institution_ids":["https://openalex.org/I2252078561"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057613852","display_name":"Peizhao Zhang","orcid":"https://orcid.org/0000-0001-7128-191X"},"institutions":[{"id":"https://openalex.org/I2252078561","display_name":"Meta (Israel)","ror":"https://ror.org/02388em19","country_code":"IL","type":"company","lineage":["https://openalex.org/I2252078561","https://openalex.org/I4210114444"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Peizhao Zhang","raw_affiliation_strings":["Facebook AI"],"affiliations":[{"raw_affiliation_string":"Facebook AI","institution_ids":["https://openalex.org/I2252078561"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106668475","display_name":"Yuandong Tian","orcid":null},"institutions":[{"id":"https://openalex.org/I2252078561","display_name":"Meta (Israel)","ror":"https://ror.org/02388em19","country_code":"IL","type":"company","lineage":["https://openalex.org/I2252078561","https://openalex.org/I4210114444"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Yuandong Tian","raw_affiliation_strings":["Facebook AI"],"affiliations":[{"raw_affiliation_string":"Facebook AI","institution_ids":["https://openalex.org/I2252078561"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120863457","display_name":"BoRui Wu","orcid":"https://orcid.org/0000-0002-2649-5561"},"institutions":[{"id":"https://openalex.org/I2252078561","display_name":"Meta (Israel)","ror":"https://ror.org/02388em19","country_code":"IL","type":"company","lineage":["https://openalex.org/I2252078561","https://openalex.org/I4210114444"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Bichen Wu","raw_affiliation_strings":["Facebook AI"],"affiliations":[{"raw_affiliation_string":"Facebook AI","institution_ids":["https://openalex.org/I2252078561"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055620900","display_name":"Matt Feiszli","orcid":null},"institutions":[{"id":"https://openalex.org/I2252078561","display_name":"Meta (Israel)","ror":"https://ror.org/02388em19","country_code":"IL","type":"company","lineage":["https://openalex.org/I2252078561","https://openalex.org/I4210114444"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Matt Feiszli","raw_affiliation_strings":["Facebook AI"],"affiliations":[{"raw_affiliation_string":"Facebook AI","institution_ids":["https://openalex.org/I2252078561"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5002869474"],"corresponding_institution_ids":["https://openalex.org/I2252078561"],"apc_list":null,"apc_paid":null,"fwci":2.0174,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.88687908,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"15134","last_page":"15143"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":1.0,"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":1.0,"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":0.9994000196456909,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9990000128746033,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7919763326644897},{"id":"https://openalex.org/keywords/parsec","display_name":"Parsec","score":0.7435262203216553},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.7421057224273682},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.6033602356910706},{"id":"https://openalex.org/keywords/flops","display_name":"FLOPS","score":0.5273725986480713},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.45840173959732056},{"id":"https://openalex.org/keywords/sample-space","display_name":"Sample space","score":0.43677452206611633},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3724724352359772},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.323976993560791},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.2165357768535614},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.131798654794693}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7919763326644897},{"id":"https://openalex.org/C44060867","wikidata":"https://www.wikidata.org/wiki/Q12129","display_name":"Parsec","level":3,"score":0.7435262203216553},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.7421057224273682},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.6033602356910706},{"id":"https://openalex.org/C3826847","wikidata":"https://www.wikidata.org/wiki/Q188768","display_name":"FLOPS","level":2,"score":0.5273725986480713},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.45840173959732056},{"id":"https://openalex.org/C100279318","wikidata":"https://www.wikidata.org/wiki/Q467440","display_name":"Sample space","level":2,"score":0.43677452206611633},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3724724352359772},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.323976993560791},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.2165357768535614},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.131798654794693},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C150846664","wikidata":"https://www.wikidata.org/wiki/Q7602306","display_name":"Stars","level":2,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cvpr46437.2021.01489","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr46437.2021.01489","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":79,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1821462560","https://openalex.org/W1972972727","https://openalex.org/W2097117768","https://openalex.org/W2163605009","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2274287116","https://openalex.org/W2331143823","https://openalex.org/W2547875792","https://openalex.org/W2549139847","https://openalex.org/W2553303224","https://openalex.org/W2594529350","https://openalex.org/W2752782242","https://openalex.org/W2810075754","https://openalex.org/W2883780447","https://openalex.org/W2885820039","https://openalex.org/W2913618604","https://openalex.org/W2949264490","https://openalex.org/W2949736877","https://openalex.org/W2951104886","https://openalex.org/W2955425717","https://openalex.org/W2960010704","https://openalex.org/W2962746461","https://openalex.org/W2962861284","https://openalex.org/W2963125010","https://openalex.org/W2963163009","https://openalex.org/W2963420686","https://openalex.org/W2963446712","https://openalex.org/W2963778169","https://openalex.org/W2963918968","https://openalex.org/W2964081807","https://openalex.org/W2964121744","https://openalex.org/W2964259004","https://openalex.org/W2964350391","https://openalex.org/W2965658867","https://openalex.org/W2967733054","https://openalex.org/W2971107871","https://openalex.org/W2971302065","https://openalex.org/W2980137827","https://openalex.org/W2981698279","https://openalex.org/W2982083293","https://openalex.org/W2995999070","https://openalex.org/W3016719260","https://openalex.org/W3034609471","https://openalex.org/W3035087309","https://openalex.org/W3040385575","https://openalex.org/W3109946440","https://openalex.org/W3113272803","https://openalex.org/W4288320011","https://openalex.org/W4297665946","https://openalex.org/W4300687381","https://openalex.org/W6631190155","https://openalex.org/W6638523607","https://openalex.org/W6684191040","https://openalex.org/W6694260854","https://openalex.org/W6701947533","https://openalex.org/W6725739302","https://openalex.org/W6729448088","https://openalex.org/W6729956949","https://openalex.org/W6734593296","https://openalex.org/W6740474667","https://openalex.org/W6741414320","https://openalex.org/W6743731764","https://openalex.org/W6745614327","https://openalex.org/W6748057086","https://openalex.org/W6750719829","https://openalex.org/W6752515464","https://openalex.org/W6753344092","https://openalex.org/W6753767121","https://openalex.org/W6756887525","https://openalex.org/W6758740788","https://openalex.org/W6762718338","https://openalex.org/W6764013109","https://openalex.org/W6767701525","https://openalex.org/W6771654589","https://openalex.org/W6772755080","https://openalex.org/W6775845032","https://openalex.org/W6787227670"],"related_works":["https://openalex.org/W2152436418","https://openalex.org/W2038229768","https://openalex.org/W2169875292","https://openalex.org/W4382323155","https://openalex.org/W4315697128","https://openalex.org/W4387670984","https://openalex.org/W2950411467","https://openalex.org/W2208151106","https://openalex.org/W3205506801","https://openalex.org/W2657535882"],"abstract_inverted_index":{"Differential":[0],"Neural":[1],"Architecture":[2],"Search":[3],"(NAS)":[4],"requires":[5],"all":[6],"layer":[7],"choices":[8],"to":[9,47,55,79,86,99,175,181,244],"be":[10,182],"held":[11],"in":[12,65,102],"memory":[13,44],"simultaneously;":[14],"this":[15,135],"limits":[16],"the":[17,80,90,103,117,122,164,177,199,202,221],"size":[18,211],"of":[19,124,131,204,210],"both":[20],"search":[21,100,151,200,240],"space":[22,180],"and":[23,39,92,150,163,188,197,220],"final":[24],"architecture.":[25],"In":[26],"contrast,":[27],"Probabilistic":[28,138],"NAS,":[29],"such":[30],"as":[31,42,45,95],"PARSEC,":[32,143],"learns":[33],"a":[34,49,75,108,113,208],"distribution":[35,81,115],"over":[36,128,201],"high-performing":[37],"architectures,":[38,58],"uses":[40],"only":[41],"much":[43],"needed":[46],"train":[48],"single":[50],"model.":[51],"Nevertheless,":[52],"it":[53,60,144],"needs":[54],"sample":[56,146],"many":[57],"making":[59],"computationally":[61],"expensive":[62],"for":[63],"searching":[64,207],"an":[66,129],"extensive":[67],"space.":[68],"To":[69],"solve":[70],"these":[71],"problems,":[72],"we":[73,106,238],"propose":[74,107],"sampling":[76],"method":[77,136],"adaptive":[78],"entropy,":[82],"drawing":[83],"more":[84,191],"samples":[85,94],"encourage":[87],"explorations":[88],"at":[89,116],"beginning,":[91],"reducing":[93],"learning":[96],"proceeds.":[97],"Furthermore,":[98],"fast":[101],"multivariate":[104],"space,":[105],"coarse-to-fine":[109],"strategy":[110],"by":[111,127,227,259],"using":[112,231,262],"factorized":[114],"beginning":[118],"which":[119],"can":[120,145],"reduce":[121],"number":[123,203],"architecture":[125,233],"parameters":[126],"order":[130],"magnitude.":[132],"We":[133],"call":[134],"Fast":[137],"NAS":[139],"(FP-NAS).":[140],"Compared":[141,154],"with":[142,155,250,255],"64%":[147],"fewer":[148],"architectures":[149],"2.1\u00d7":[152],"faster.":[153],"FBNetV2,":[156],"FP-NAS":[157,172,214],"is":[158,215],"1.9\u00d7":[159],"-":[160],"3.5":[161],"\u00d7faster,":[162],"searched":[165,222],"models":[166,169,242],"outperform":[167],"FBNetV2":[168,179],"on":[170],"ImageNet.":[171],"allows":[173],"us":[174],"expand":[176],"giant":[178],"wider":[183],"(i.e.":[184,190],"larger":[185],"channel":[186],"choices)":[187],"deeper":[189],"blocks),":[192],"while":[193],"adding":[194],"Split-Attention":[195],"block":[196],"enabling":[198],"splits.":[205],"When":[206],"model":[209,224,249],"0.4G":[212],"FLOPS,":[213],"132\u00d7":[216],"faster":[217],"than":[218],"EfficientNet,":[219],"FP-NAS-L0":[223],"outperforms":[225],"EfficientNet-B0":[226],"0.7%":[228,260],"accuracy.":[229],"Without":[230],"any":[232],"surrogate":[234],"or":[235],"scaling":[236],"tricks,":[237],"directly":[239],"large":[241],"up":[243],"1.0G":[245],"FLOPS.":[246,264],"Our":[247],"FP-NAS-L2":[248],"simple":[251],"distillation":[252,258],"out-performs":[253],"BigNAS-XL":[254],"advanced":[256],"inplace":[257],"accuracy":[261],"similar":[263]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":2}],"updated_date":"2026-01-11T23:08:45.486102","created_date":"2025-10-10T00:00:00"}