乐胖代购免代理版

{"id":"https://openalex.org/W2922410253","doi":"https://doi.org/10.1109/cvpr.2019.00927","title":"EIGEN: Ecologically-Inspired GENetic Approach for Neural Network Structure Searching From Scratch","display_name":"EIGEN: Ecologically-Inspired GENetic Approach for Neural Network Structure Searching From Scratch","publication_year":2019,"publication_date":"2019-06-01","ids":{"openalex":"https://openalex.org/W2922410253","doi":"https://doi.org/10.1109/cvpr.2019.00927","mag":"2922410253"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2019.00927","pdf_url":null,"source":{"id":"https://openalex.org/S4363607701","display_name":"2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1806.01940","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101823378","display_name":"Jian Ren","orcid":"https://orcid.org/0000-0001-7924-9586"},"institutions":[{"id":"https://openalex.org/I4210096112","display_name":"Rutgers Sexual and Reproductive Health and Rights","ror":"https://ror.org/00rcvgx40","country_code":"NL","type":"other","lineage":["https://openalex.org/I4210096112"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Jian Ren","raw_affiliation_strings":["Rutgers University"],"affiliations":[{"raw_affiliation_string":"Rutgers University","institution_ids":["https://openalex.org/I4210096112"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100356606","display_name":"Zhe Li","orcid":"https://orcid.org/0000-0001-7056-4133"},"institutions":[{"id":"https://openalex.org/I126307644","display_name":"University of Iowa","ror":"https://ror.org/036jqmy94","country_code":"US","type":"education","lineage":["https://openalex.org/I126307644"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhe Li","raw_affiliation_strings":["The University of Iowa"],"affiliations":[{"raw_affiliation_string":"The University of Iowa","institution_ids":["https://openalex.org/I126307644"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100381753","display_name":"Shuicheng Yan","orcid":"https://orcid.org/0000-0001-8906-3777"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jianchao Yang","raw_affiliation_strings":["Bytedance AI Lab"],"affiliations":[{"raw_affiliation_string":"Bytedance AI Lab","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101773973","display_name":"Ning Xu","orcid":"https://orcid.org/0000-0001-8910-0937"},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ning Xu","raw_affiliation_strings":["Amazon Go"],"affiliations":[{"raw_affiliation_string":"Amazon Go","institution_ids":["https://openalex.org/I1311688040"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023288846","display_name":"Tianbao Yang","orcid":"https://orcid.org/0000-0002-7858-5438"},"institutions":[{"id":"https://openalex.org/I126307644","display_name":"University of Iowa","ror":"https://ror.org/036jqmy94","country_code":"US","type":"education","lineage":["https://openalex.org/I126307644"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tianbao Yang","raw_affiliation_strings":["The University of Iowa"],"affiliations":[{"raw_affiliation_string":"The University of Iowa","institution_ids":["https://openalex.org/I126307644"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089373018","display_name":"David J. Foran","orcid":"https://orcid.org/0000-0002-0090-0055"},"institutions":[{"id":"https://openalex.org/I4210096112","display_name":"Rutgers Sexual and Reproductive Health and Rights","ror":"https://ror.org/00rcvgx40","country_code":"NL","type":"other","lineage":["https://openalex.org/I4210096112"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"David J. Foran","raw_affiliation_strings":["Rutgers University"],"affiliations":[{"raw_affiliation_string":"Rutgers University","institution_ids":["https://openalex.org/I4210096112"]}]}],"institution_assertions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.661,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.728618,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":92},"biblio":{"volume":null,"issue":null,"first_page":"9051","last_page":"9060"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.999,"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":0.999,"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":0.9982,"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/T12676","display_name":"Machine Learning and ELM","score":0.9979,"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/scratch","display_name":"Scratch","score":0.64125085}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.77048284},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6574216},{"id":"https://openalex.org/C2781235140","wikidata":"https://www.wikidata.org/wiki/Q275131","display_name":"Scratch","level":2,"score":0.64125085},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5907732},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.5589642},{"id":"https://openalex.org/C105902424","wikidata":"https://www.wikidata.org/wiki/Q1197129","display_name":"Evolutionary computation","level":2,"score":0.49798632},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48341},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.47865403},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.465047},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.45847514},{"id":"https://openalex.org/C7863114","wikidata":"https://www.wikidata.org/wiki/Q192627","display_name":"Mimicry","level":2,"score":0.44868293},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.41277263},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06972125},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.06455213},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","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/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2019.00927","pdf_url":null,"source":{"id":"https://openalex.org/S4363607701","display_name":"2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/1806.01940","pdf_url":"https://arxiv.org/pdf/1806.01940","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/1806.01940","pdf_url":"https://arxiv.org/pdf/1806.01940","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":61,"referenced_works":["https://openalex.org/W1536680647","https://openalex.org/W1686810756","https://openalex.org/W1690739335","https://openalex.org/W1821462560","https://openalex.org/W1836465849","https://openalex.org/W1971231926","https://openalex.org/W2004445927","https://openalex.org/W2111935653","https://openalex.org/W2113207845","https://openalex.org/W2123045220","https://openalex.org/W2135950684","https://openalex.org/W2163605009","https://openalex.org/W2168894214","https://openalex.org/W2194775991","https://openalex.org/W2266822037","https://openalex.org/W2294370754","https://openalex.org/W2402144811","https://openalex.org/W2553303224","https://openalex.org/W2587014634","https://openalex.org/W2589973949","https://openalex.org/W2593744649","https://openalex.org/W2594529350","https://openalex.org/W2606006859","https://openalex.org/W2739879705","https://openalex.org/W2747469359","https://openalex.org/W2748513770","https://openalex.org/W2751836095","https://openalex.org/W2769653148","https://openalex.org/W2773706593","https://openalex.org/W2782417188","https://openalex.org/W2794411182","https://openalex.org/W2796265726","https://openalex.org/W2803311163","https://openalex.org/W2805975663","https://openalex.org/W2810075754","https://openalex.org/W2885820039","https://openalex.org/W2886200920","https://openalex.org/W2949117887","https://openalex.org/W2949264490","https://openalex.org/W2951104886","https://openalex.org/W2953384591","https://openalex.org/W2962746461","https://openalex.org/W2963137684","https://openalex.org/W2963382180","https://openalex.org/W2963446712","https://openalex.org/W2963473542","https://openalex.org/W2963525613","https://openalex.org/W2963536136","https://openalex.org/W2963759595","https://openalex.org/W2963778169","https://openalex.org/W2963821229","https://openalex.org/W2964081807","https://openalex.org/W2964118293","https://openalex.org/W2964294659","https://openalex.org/W2965658867","https://openalex.org/W3001340915","https://openalex.org/W3118608800","https://openalex.org/W4255158661","https://openalex.org/W4295185264","https://openalex.org/W4297778814","https://openalex.org/W4300687381"],"related_works":["https://openalex.org/W2770018148","https://openalex.org/W2566749067","https://openalex.org/W2475116013","https://openalex.org/W2385135707","https://openalex.org/W2379994817","https://openalex.org/W2358308169","https://openalex.org/W2332959588","https://openalex.org/W2159218316","https://openalex.org/W2066741154","https://openalex.org/W1980659691"],"abstract_inverted_index":{"Designing":[0],"the":[1,10,25,40,66,75,111,114,131,137,141,154,184,195],"structure":[2,53],"of":[3,9,42,89,143,157,161],"neural":[4,51,92],"networks":[5,112,139],"is":[6,20,118,128,150],"considered":[7],"one":[8],"most":[11],"challenging":[12],"tasks":[13],"in":[14,120,217,224],"deep":[15],"learning,":[16],"especially":[17],"when":[18],"there":[19],"few":[21,62],"prior":[22,72],"knowledge":[23,73],"about":[24,74],"task":[26,76],"domain.":[27,77],"In":[28],"this":[29],"paper,":[30],"we":[31,69,79],"propose":[32],"an":[33],"Ecologically-Inspired":[34],"GENetic":[35],"(EIGEN)":[36],"approach":[37,175,200],"that":[38,172],"uses":[39],"concept":[41],"succession,":[43],"extinction,":[44],"mimicry,":[45],"and":[46,61,147],"gene":[47,148],"duplication":[48,149],"to":[49,84,123,135,152,164,183,213],"search":[50],"network":[52,60,93,146,167,196],"from":[54,113],"scratch":[55],"with":[56,188],"poorly":[57,90],"initialized":[58,91],"simple":[59],"constraints":[63],"forced":[64],"during":[65,130],"evolution,":[67],"as":[68],"assume":[70],"no":[71],"Specifically,":[78],"first":[80],"use":[81],"primary":[82,115],"succession":[83,104],"rapidly":[85],"evolve":[86],"a":[87,96,102,144],"population":[88],"structures":[94],"into":[95],"more":[97,218],"diverse":[98],"population,":[99],"followed":[100],"by":[101,198],"secondary":[103],"stage":[105],"for":[106],"fine-grained":[107],"searching":[108],"based":[109],"on":[110,201],"succession.":[116],"Extinction":[117],"applied":[119],"both":[121,160],"stages":[122],"reduce":[124],"computational":[125],"cost.":[126,192],"Mimicry":[127],"employed":[129],"entire":[132],"evolution":[133],"process":[134],"help":[136,163],"inferior":[138],"imitate":[140],"behavior":[142],"superior":[145],"utilized":[151],"duplicate":[153],"learned":[155],"blocks":[156],"novel":[158],"structures,":[159],"which":[162],"find":[165],"better":[166,180],"structures.":[168],"Experimental":[169],"results":[170],"show":[171],"our":[173,199],"proposed":[174],"can":[176],"achieve":[177],"similar":[178],"or":[179],"performance":[181],"compared":[182,212],"existing":[185],"genetic":[186],"approaches":[187],"dramatically":[189],"reduced":[190],"computation":[191],"For":[193],"example,":[194],"discovered":[197],"CIFAR-100":[202],"dataset":[203],"achieves":[204],"78.1%":[205],"test":[206,215],"accuracy":[207,216],"under":[208],"120":[209],"GPU":[210,222],"hours,":[211],"77.0%":[214],"than":[219],"65,":[220],"536":[221],"hours":[223],"[35].":[225]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2922410253","counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":4}],"updated_date":"2025-01-23T03:34:09.667701","created_date":"2019-03-22"}