乐胖代购免代理版

{"id":"https://openalex.org/W4229027123","doi":"https://doi.org/10.1109/percomworkshops53856.2022.9767369","title":"Federated Self-Supervised Learning in Heterogeneous Settings: Limits of a Baseline Approach on HAR","display_name":"Federated Self-Supervised Learning in Heterogeneous Settings: Limits of a Baseline Approach on HAR","publication_year":2022,"publication_date":"2022-03-21","ids":{"openalex":"https://openalex.org/W4229027123","doi":"https://doi.org/10.1109/percomworkshops53856.2022.9767369"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/percomworkshops53856.2022.9767369","pdf_url":null,"source":{"id":"https://openalex.org/S4363608020","display_name":"2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)","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":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2207.08187","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5033506974","display_name":"Sannara Ek","orcid":null},"institutions":[{"id":"https://openalex.org/I4210104430","display_name":"Laboratoire d'Informatique de Grenoble","ror":"https://ror.org/01c8rcg82","country_code":"FR","type":"facility","lineage":["https://openalex.org/I106785703","https://openalex.org/I1294671590","https://openalex.org/I1326498283","https://openalex.org/I4210104430","https://openalex.org/I4210159245","https://openalex.org/I899635006"]},{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I899635006","display_name":"Universit\u00e9 Grenoble Alpes","ror":"https://ror.org/02rx3b187","country_code":"FR","type":"education","lineage":["https://openalex.org/I899635006"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Sannara Ek","raw_affiliation_strings":["Univ. Grenoble Alpes,CNRS,Grenoble,France,LIG F-38000"],"affiliations":[{"raw_affiliation_string":"Univ. Grenoble Alpes,CNRS,Grenoble,France,LIG F-38000","institution_ids":["https://openalex.org/I4210104430","https://openalex.org/I1294671590","https://openalex.org/I899635006"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087133999","display_name":"Romain Rombourg","orcid":null},"institutions":[{"id":"https://openalex.org/I4210104430","display_name":"Laboratoire d'Informatique de Grenoble","ror":"https://ror.org/01c8rcg82","country_code":"FR","type":"facility","lineage":["https://openalex.org/I106785703","https://openalex.org/I1294671590","https://openalex.org/I1326498283","https://openalex.org/I4210104430","https://openalex.org/I4210159245","https://openalex.org/I899635006"]},{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I899635006","display_name":"Universit\u00e9 Grenoble Alpes","ror":"https://ror.org/02rx3b187","country_code":"FR","type":"education","lineage":["https://openalex.org/I899635006"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Romain Rombourg","raw_affiliation_strings":["Univ. Grenoble Alpes,CNRS,Grenoble,France,LIG F-38000"],"affiliations":[{"raw_affiliation_string":"Univ. Grenoble Alpes,CNRS,Grenoble,France,LIG F-38000","institution_ids":["https://openalex.org/I4210104430","https://openalex.org/I1294671590","https://openalex.org/I899635006"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079066445","display_name":"Fran\u00e7ois Portet","orcid":"https://orcid.org/0000-0003-2542-0661"},"institutions":[{"id":"https://openalex.org/I4210104430","display_name":"Laboratoire d'Informatique de Grenoble","ror":"https://ror.org/01c8rcg82","country_code":"FR","type":"facility","lineage":["https://openalex.org/I106785703","https://openalex.org/I1294671590","https://openalex.org/I1326498283","https://openalex.org/I4210104430","https://openalex.org/I4210159245","https://openalex.org/I899635006"]},{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I899635006","display_name":"Universit\u00e9 Grenoble Alpes","ror":"https://ror.org/02rx3b187","country_code":"FR","type":"education","lineage":["https://openalex.org/I899635006"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Francois Portet","raw_affiliation_strings":["Univ. Grenoble Alpes,CNRS,Grenoble,France,LIG F-38000"],"affiliations":[{"raw_affiliation_string":"Univ. Grenoble Alpes,CNRS,Grenoble,France,LIG F-38000","institution_ids":["https://openalex.org/I4210104430","https://openalex.org/I1294671590","https://openalex.org/I899635006"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001683117","display_name":"Philippe Lalanda","orcid":"https://orcid.org/0000-0002-8185-2605"},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I899635006","display_name":"Universit\u00e9 Grenoble Alpes","ror":"https://ror.org/02rx3b187","country_code":"FR","type":"education","lineage":["https://openalex.org/I899635006"]},{"id":"https://openalex.org/I4210104430","display_name":"Laboratoire d'Informatique de Grenoble","ror":"https://ror.org/01c8rcg82","country_code":"FR","type":"facility","lineage":["https://openalex.org/I106785703","https://openalex.org/I1294671590","https://openalex.org/I1326498283","https://openalex.org/I4210104430","https://openalex.org/I4210159245","https://openalex.org/I899635006"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Philippe Lalanda","raw_affiliation_strings":["Univ. Grenoble Alpes,CNRS,Grenoble,France,LIG F-38000"],"affiliations":[{"raw_affiliation_string":"Univ. Grenoble Alpes,CNRS,Grenoble,France,LIG F-38000","institution_ids":["https://openalex.org/I1294671590","https://openalex.org/I899635006","https://openalex.org/I4210104430"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.619,"has_fulltext":true,"fulltext_origin":"pdf","cited_by_count":4,"citation_normalized_percentile":{"value":0.281132,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":80,"max":82},"biblio":{"volume":null,"issue":null,"first_page":"557","last_page":"562"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9995,"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"}},"topics":[{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9995,"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9897,"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9804,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/autoencoder","display_name":"Autoencoder","score":0.72700703},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated Learning","score":0.7026008},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised Learning","score":0.5438971},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.47343114},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature Learning","score":0.46975115},{"id":"https://openalex.org/keywords/representation","display_name":"Representation","score":0.44960457}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.81199944},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.7717558},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.73819435},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.72700703},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.7026008},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.6865355},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.5438971},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.47343114},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.46975115},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.44960457},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.4206168},{"id":"https://openalex.org/C66882249","wikidata":"https://www.wikidata.org/wiki/Q169336","display_name":"Homogeneous","level":2,"score":0.41295943},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.35385612},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.12029663},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"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/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/percomworkshops53856.2022.9767369","pdf_url":null,"source":{"id":"https://openalex.org/S4363608020","display_name":"2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)","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":false,"landing_page_url":"https://hal.science/hal-03727244","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2207.08187","pdf_url":"https://arxiv.org/pdf/2207.08187","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":false,"landing_page_url":"https://api.datacite.org/dois/10.48550/arxiv.2207.08187","pdf_url":null,"source":{"id":"https://openalex.org/S4393179698","display_name":"DataCite API","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/I4210145204","host_organization_name":"DataCite","host_organization_lineage":["https://openalex.org/I4210145204"],"host_organization_lineage_names":["DataCite"],"type":"metadata"},"license":null,"license_id":null,"version":null}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2207.08187","pdf_url":"https://arxiv.org/pdf/2207.08187","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":["https://openalex.org/W4229027123"],"referenced_works_count":23,"referenced_works":["https://openalex.org/W134960717","https://openalex.org/W2057907879","https://openalex.org/W2181347294","https://openalex.org/W2340025709","https://openalex.org/W2553915786","https://openalex.org/W2759690896","https://openalex.org/W2883766876","https://openalex.org/W2897943474","https://openalex.org/W2900120080","https://openalex.org/W2905388940","https://openalex.org/W2916267633","https://openalex.org/W2972497135","https://openalex.org/W3005680577","https://openalex.org/W3006017224","https://openalex.org/W3026182744","https://openalex.org/W3035524453","https://openalex.org/W3038022836","https://openalex.org/W3098250197","https://openalex.org/W3205701848","https://openalex.org/W3209696639","https://openalex.org/W4297808394","https://openalex.org/W4318619660","https://openalex.org/W4394646653"],"related_works":["https://openalex.org/W4389832810","https://openalex.org/W4313561566","https://openalex.org/W4281663961","https://openalex.org/W4220682630","https://openalex.org/W3208888551","https://openalex.org/W3208386644","https://openalex.org/W3181622257","https://openalex.org/W3163146846","https://openalex.org/W2983142544","https://openalex.org/W2891059443"],"abstract_inverted_index":{"Federated":[0,162,189],"Learning":[1,109,146,149,192],"is":[2,24,51,104],"a":[3,41,75,141,151,167,183],"new":[4],"machine":[5],"learning":[6,12,23,86,93],"paradigm":[7],"dealing":[8],"with":[9,40,122,147,174],"distributed":[10],"model":[11],"on":[13,29,91,202],"independent":[14],"devices.":[15,204],"One":[16],"of":[17,21,47,77,99,132,144,197],"the":[18,45,54,123,129,138,195],"many":[19,67],"advantages":[20],"federated":[22,85,108,145],"that":[25,88,119,156],"training":[26],"data":[27,78,200],"stay":[28],"devices":[30],"(such":[31],"as":[32,70],"smartphones),":[33],"and":[34,64,81,160],"only":[35],"learned":[36],"models":[37],"are":[38,111],"shared":[39],"centralized":[42],"server.":[43],"In":[44],"case":[46],"supervised":[48,92],"learning,":[49],"labeling":[50],"entrusted":[52],"to":[53,113,128,165,193],"clients.":[55],"However,":[56],"acquiring":[57],"such":[58,69],"labels":[59],"can":[60],"be":[61],"prohibitively":[62],"expensive":[63],"error-prone":[65],"for":[66,140,170,182],"tasks,":[68],"human":[71],"activity":[72],"recognition.":[73],"Hence,":[74],"wealth":[76],"remains":[79],"unlabelled":[80,100,199],"unexploited.":[82],"Most":[83],"existing":[84],"approaches":[87,110],"focus":[89],"mainly":[90],"have":[94,120,125],"mostly":[95],"ignored":[96],"this":[97],"mass":[98,196],"data.":[101],"Furthermore,":[102],"it":[103],"unclear":[105],"whether":[106],"standard":[107,157,161],"suited":[112],"self-supervised":[114],"learning.":[115],"The":[116],"few":[117],"studies":[118],"dealt":[121],"problem":[124],"limited":[126],"themselves":[127],"favorable":[130],"situation":[131],"homogeneous":[133],"datasets.":[134,178],"This":[135],"work":[136],"lays":[137],"groundwork":[139],"reference":[142],"evaluation":[143],"Semi-Supervised":[148],"in":[150,188],"realistic":[152,176],"setting.":[153],"We":[154],"show":[155],"lightweight":[158],"autoencoder":[159],"Averaging":[163],"fail":[164],"learn":[166],"robust":[168],"representation":[169],"Human":[171],"Activity":[172],"Recognition":[173],"several":[175],"heterogeneous":[177,198],"These":[179],"findings":[180],"advocate":[181],"more":[184],"intensive":[185],"research":[186],"effort":[187],"Self":[190],"Supervised":[191],"exploit":[194],"present":[201],"mobile":[203]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4229027123","counts_by_year":[{"year":2024,"cited_by_count":4}],"updated_date":"2025-01-20T11:28:52.507891","created_date":"2022-05-08"}