乐胖代购免代理版

{"id":"https://openalex.org/W4365397863","doi":"https://doi.org/10.1137/1.9781611977653.ch81","title":"A General-Purpose Transferable Predictor for Neural Architecture Search","display_name":"A General-Purpose Transferable Predictor for Neural Architecture Search","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4365397863","doi":"https://doi.org/10.1137/1.9781611977653.ch81"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1137/1.9781611977653.ch81","pdf_url":null,"source":{"id":"https://openalex.org/S4306463922","display_name":"Society for Industrial and Applied Mathematics eBooks","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"ebook platform"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"book-chapter","type_crossref":"book-chapter","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2302.10835","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103231191","display_name":"Fred X. Han","orcid":"https://orcid.org/0000-0001-9379-2147"},"institutions":[{"id":"https://openalex.org/I4210115038","display_name":"Huawei Technologies (Canada)","ror":"https://ror.org/026venb53","country_code":"CA","type":"company","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210115038"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Fred X. Han","raw_affiliation_strings":["Huawei Technologies Canada, Edmonton,"],"affiliations":[{"raw_affiliation_string":"Huawei Technologies Canada, Edmonton,","institution_ids":["https://openalex.org/I4210115038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044090050","display_name":"Keith G. Mills","orcid":"https://orcid.org/0000-0001-6054-1798"},"institutions":[{"id":"https://openalex.org/I154425047","display_name":"University of Alberta","ror":"https://ror.org/0160cpw27","country_code":"CA","type":"education","lineage":["https://openalex.org/I154425047"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Keith G. Mills","raw_affiliation_strings":["University of Alberta,"],"affiliations":[{"raw_affiliation_string":"University of Alberta,","institution_ids":["https://openalex.org/I154425047"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110284741","display_name":"Fabi\u00e1n A. Chudak","orcid":null},"institutions":[{"id":"https://openalex.org/I4210115038","display_name":"Huawei Technologies (Canada)","ror":"https://ror.org/026venb53","country_code":"CA","type":"company","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210115038"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Fabian Chudak","raw_affiliation_strings":["Huawei Technologies Canada, Edmonton,"],"affiliations":[{"raw_affiliation_string":"Huawei Technologies Canada, Edmonton,","institution_ids":["https://openalex.org/I4210115038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050823596","display_name":"Parsa Riahi","orcid":null},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Parsa Riahi","raw_affiliation_strings":["University of British Columbia,"],"affiliations":[{"raw_affiliation_string":"University of British Columbia,","institution_ids":["https://openalex.org/I141945490"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006778208","display_name":"Mohammad Salameh","orcid":"https://orcid.org/0000-0001-9266-4637"},"institutions":[{"id":"https://openalex.org/I4210115038","display_name":"Huawei Technologies (Canada)","ror":"https://ror.org/026venb53","country_code":"CA","type":"company","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210115038"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Mohammad Salameh","raw_affiliation_strings":["Huawei Technologies Canada, Edmonton,"],"affiliations":[{"raw_affiliation_string":"Huawei Technologies Canada, Edmonton,","institution_ids":["https://openalex.org/I4210115038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100333626","display_name":"Jialin Zhang","orcid":"https://orcid.org/0000-0002-6245-1013"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]},{"id":"https://openalex.org/I2802592688","display_name":"Kirin (Japan)","ror":"https://ror.org/0586k5242","country_code":"JP","type":"company","lineage":["https://openalex.org/I2802592688"]}],"countries":["CN","JP"],"is_corresponding":false,"raw_author_name":"Jialin Zhang","raw_affiliation_strings":["Huawei Kirin Solution, Shanghai"],"affiliations":[{"raw_affiliation_string":"Huawei Kirin Solution, Shanghai","institution_ids":["https://openalex.org/I2250955327","https://openalex.org/I2802592688"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005328001","display_name":"Wei L\u00fc","orcid":"https://orcid.org/0000-0003-0829-5440"},"institutions":[{"id":"https://openalex.org/I4210115038","display_name":"Huawei Technologies (Canada)","ror":"https://ror.org/026venb53","country_code":"CA","type":"company","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210115038"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Wei Lu","raw_affiliation_strings":["Huawei Technologies Canada, Edmonton,"],"affiliations":[{"raw_affiliation_string":"Huawei Technologies Canada, Edmonton,","institution_ids":["https://openalex.org/I4210115038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012650575","display_name":"Shangling Jui","orcid":"https://orcid.org/0000-0002-1047-4264"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]},{"id":"https://openalex.org/I2802592688","display_name":"Kirin (Japan)","ror":"https://ror.org/0586k5242","country_code":"JP","type":"company","lineage":["https://openalex.org/I2802592688"]}],"countries":["CN","JP"],"is_corresponding":false,"raw_author_name":"Shangling Jui","raw_affiliation_strings":["Huawei Kirin Solution, Shanghai"],"affiliations":[{"raw_affiliation_string":"Huawei Kirin Solution, Shanghai","institution_ids":["https://openalex.org/I2250955327","https://openalex.org/I2802592688"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032424832","display_name":"Di Niu","orcid":"https://orcid.org/0000-0002-5250-7327"},"institutions":[{"id":"https://openalex.org/I154425047","display_name":"University of Alberta","ror":"https://ror.org/0160cpw27","country_code":"CA","type":"education","lineage":["https://openalex.org/I154425047"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Di Niu","raw_affiliation_strings":["University of Alberta,"],"affiliations":[{"raw_affiliation_string":"University of Alberta,","institution_ids":["https://openalex.org/I154425047"]}]}],"institution_assertions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.85,"has_fulltext":true,"fulltext_origin":"pdf","cited_by_count":1,"citation_normalized_percentile":{"value":0.685528,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":67,"max":78},"biblio":{"volume":null,"issue":null,"first_page":"721","last_page":"729"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9989,"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":0.9989,"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":0.996,"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":0.9957,"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/representation","display_name":"Representation","score":0.43930614}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.68101263},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.57298017},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.5697145},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.56316656},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5351618},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5271128},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.49940252},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.4807584},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.43930614},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.41793114},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.37447006},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.340063},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1137/1.9781611977653.ch81","pdf_url":null,"source":{"id":"https://openalex.org/S4306463922","display_name":"Society for Industrial and Applied Mathematics eBooks","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"ebook platform"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2302.10835","pdf_url":"https://arxiv.org/pdf/2302.10835","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2302.10835","pdf_url":"http://arxiv.org/pdf/2302.10835","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2302.10835","pdf_url":"https://arxiv.org/pdf/2302.10835","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":34,"referenced_works":["https://openalex.org/W2412782625","https://openalex.org/W2894740066","https://openalex.org/W2951104886","https://openalex.org/W2951245151","https://openalex.org/W2962746461","https://openalex.org/W2962810718","https://openalex.org/W2963163009","https://openalex.org/W2964081807","https://openalex.org/W2964515685","https://openalex.org/W2981406437","https://openalex.org/W2994749257","https://openalex.org/W3002687113","https://openalex.org/W3005680577","https://openalex.org/W3005842225","https://openalex.org/W3006236094","https://openalex.org/W3007549584","https://openalex.org/W3013310686","https://openalex.org/W3035715446","https://openalex.org/W3094801149","https://openalex.org/W3096533519","https://openalex.org/W3100859887","https://openalex.org/W3104688113","https://openalex.org/W3113177135","https://openalex.org/W3121924028","https://openalex.org/W3166395393","https://openalex.org/W3191225462","https://openalex.org/W3209022794","https://openalex.org/W4239072543","https://openalex.org/W4287686213","https://openalex.org/W4287715829","https://openalex.org/W4287812705","https://openalex.org/W4287907702","https://openalex.org/W4295312788","https://openalex.org/W4385245566"],"related_works":["https://openalex.org/W51364034","https://openalex.org/W4313906399","https://openalex.org/W4293226380","https://openalex.org/W2915512527","https://openalex.org/W2798997222","https://openalex.org/W2798198862","https://openalex.org/W2793336762","https://openalex.org/W2303858293","https://openalex.org/W2188500270","https://openalex.org/W2091548507"],"abstract_inverted_index":{"Understanding":[0],"and":[1,24,31,55,115,146,174,205],"modelling":[2],"the":[3,124,149],"performance":[4,34,139],"of":[5,101,127,151],"neural":[6,75,194],"architectures":[7,129,202],"is":[8],"key":[9],"to":[10,50,60,133],"Neural":[11,91],"Architecture":[12],"Search":[13],"(NAS).":[14],"Performance":[15],"predictors":[16,41,180],"have":[17],"seen":[18],"widespread":[19],"use":[20],"in":[21,35,191],"low-cost":[22],"NAS":[23,37,78],"achieve":[25,156],"high":[26],"ranking":[27],"correlations":[28],"between":[29],"predicted":[30],"ground":[32],"truth":[33],"several":[36,169],"benchmarks.":[38],"However,":[39],"existing":[40],"are":[42,56,177],"often":[43],"designed":[44],"based":[45],"on":[46,143,164,203,215],"network":[47,109],"encodings":[48],"specific":[49],"a":[51,73,95,117,207],"predefined":[52],"search":[53,62,83,166,182,196],"space":[54],"therefore":[57],"not":[58],"generalizable":[59,179],"other":[61],"spaces":[63],"or":[64],"new":[65],"architecture":[66,195,209],"families.":[67],"In":[68],"this":[69],"paper,":[70],"we":[71,155,198],"propose":[72,116],"general-purpose":[74,189],"predictor":[76,190],"for":[77,137],"that":[79,99,122,210],"can":[80,199],"transfer":[81],"across":[82,181],"spaces,":[84],"by":[85],"representing":[86],"any":[87],"given":[88],"candidate":[89],"Convolutional":[90],"Network":[92],"(CNN)":[93],"with":[94,111],"Computation":[96],"Graph":[97],"(CG)":[98],"consists":[100],"primitive":[102],"operators.":[103],"We":[104],"further":[105],"combine":[106],"our":[107,138,152,187],"CG":[108,135],"representation":[110,119],"Contrastive":[112],"Learning":[113],"(CL)":[114],"graph":[118],"learning":[120],"procedure":[121],"leverages":[123],"structural":[125],"information":[126],"unlabeled":[128],"from":[130],"multiple":[131],"families":[132],"train":[134],"embeddings":[136],"predictor.":[140],"Experimental":[141],"results":[142],"NAS-Bench-101,":[144],"201":[145],"301":[147],"demonstrate":[148],"efficacy":[150],"scheme":[153],"as":[154],"strong":[157],"positive":[158],"Spearman":[159],"Rank":[160],"Correlation":[161],"Coefficient":[162],"(SRCC)":[163],"every":[165],"space,":[167],"outperforming":[168],"Zero-Cost":[170],"Proxies,":[171],"including":[172],"Synflow":[173],"Jacov,":[175],"which":[176],"also":[178],"spaces.":[183],"Moreover,":[184],"when":[185],"using":[186],"proposed":[188],"an":[192],"evolutionary":[193],"algorithm,":[197],"find":[200,206],"highperformance":[201],"NAS-Bench-101":[204],"MobileNetV3":[208],"attains":[211],"79.2%":[212],"top-1":[213],"accuracy":[214],"ImageNet.":[216]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4365397863","counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-01-17T05:41:10.376872","created_date":"2023-04-14"}