乐胖代购免代理版

{"id":"https://openalex.org/W4313025443","doi":"https://doi.org/10.1109/cvpr52688.2022.00816","title":"Parameter-free Online Test-time Adaptation","display_name":"Parameter-free Online Test-time Adaptation","publication_year":2022,"publication_date":"2022-06-01","ids":{"openalex":"https://openalex.org/W4313025443","doi":"https://doi.org/10.1109/cvpr52688.2022.00816"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr52688.2022.00816","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_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/2201.05718","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5008594421","display_name":"Malik Boudiaf","orcid":"https://orcid.org/0000-0003-2047-6447"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Malik Boudiaf","raw_affiliation_strings":["ÉTS Montreal"],"affiliations":[{"raw_affiliation_string":"ÉTS Montreal","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064294924","display_name":"Romain Mueller","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Romain Mueller","raw_affiliation_strings":["FiveAI"],"affiliations":[{"raw_affiliation_string":"FiveAI","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053292735","display_name":"Ismail Ben Ayed","orcid":"https://orcid.org/0000-0002-9668-8027"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ismail Ben Ayed","raw_affiliation_strings":["ÉTS Montreal"],"affiliations":[{"raw_affiliation_string":"ÉTS Montreal","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009876111","display_name":"Luca Bertinetto","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luca Bertinetto","raw_affiliation_strings":["FiveAI"],"affiliations":[{"raw_affiliation_string":"FiveAI","institution_ids":[]}]}],"institution_assertions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":10.21,"has_fulltext":false,"cited_by_count":66,"citation_normalized_percentile":{"value":0.81648,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"8334","last_page":"8343"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9999,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9999,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9986,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9954,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.6440546},{"id":"https://openalex.org/keywords/heuristics","display_name":"Heuristics","score":0.5507145}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8026246},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.6810746},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.6557891},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.6440546},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5652865},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.5507145},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.53582454},{"id":"https://openalex.org/C206588197","wikidata":"https://www.wikidata.org/wiki/Q846574","display_name":"Reuse","level":2,"score":0.43006366},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.42438963},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3706206},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33877409},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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/cvpr52688.2022.00816","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_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/2201.05718","pdf_url":"https://arxiv.org/pdf/2201.05718","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":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/2201.05718","pdf_url":"https://arxiv.org/pdf/2201.05718","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":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":[{"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8","score":0.53}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":60,"referenced_works":["https://openalex.org/W1852255964","https://openalex.org/W1882958252","https://openalex.org/W1982696459","https://openalex.org/W2023060295","https://openalex.org/W2108598243","https://openalex.org/W2117539524","https://openalex.org/W2121947440","https://openalex.org/W2131953535","https://openalex.org/W2147102238","https://openalex.org/W2159291411","https://openalex.org/W2194775991","https://openalex.org/W2201792562","https://openalex.org/W2517041761","https://openalex.org/W2605102758","https://openalex.org/W2751528152","https://openalex.org/W2756073160","https://openalex.org/W2793888044","https://openalex.org/W2806187986","https://openalex.org/W2894025224","https://openalex.org/W2906405631","https://openalex.org/W2907258563","https://openalex.org/W2920725015","https://openalex.org/W2946146305","https://openalex.org/W2953816217","https://openalex.org/W2953937638","https://openalex.org/W2955425717","https://openalex.org/W2963532621","https://openalex.org/W2964275228","https://openalex.org/W2964288524","https://openalex.org/W2968638474","https://openalex.org/W2979805229","https://openalex.org/W2997701990","https://openalex.org/W2998712190","https://openalex.org/W3005680577","https://openalex.org/W3028351217","https://openalex.org/W3034218934","https://openalex.org/W3034526587","https://openalex.org/W3035235949","https://openalex.org/W3035302051","https://openalex.org/W3035701489","https://openalex.org/W3036219413","https://openalex.org/W3036825277","https://openalex.org/W3039883906","https://openalex.org/W3040002795","https://openalex.org/W3040572086","https://openalex.org/W3117088788","https://openalex.org/W3119543788","https://openalex.org/W3166396011","https://openalex.org/W3176764021","https://openalex.org/W3189951784","https://openalex.org/W3195577433","https://openalex.org/W4212977191","https://openalex.org/W4287203292","https://openalex.org/W4287204036","https://openalex.org/W4287728573","https://openalex.org/W4288083516","https://openalex.org/W4288404646","https://openalex.org/W4292779060","https://openalex.org/W4295312788","https://openalex.org/W4381059423"],"related_works":["https://openalex.org/W4390421286","https://openalex.org/W4389724018","https://openalex.org/W4360995913","https://openalex.org/W4318719684","https://openalex.org/W4318559728","https://openalex.org/W4280563792","https://openalex.org/W3183136280","https://openalex.org/W3114716045","https://openalex.org/W2775233965","https://openalex.org/W2140186469"],"abstract_inverted_index":{"Training":[0],"state-of-the-art":[1],"vision":[2],"models":[3,28,89],"has":[4],"become":[5],"prohibitively":[6],"expensive":[7],"for":[8,84,126],"researchers":[9],"and":[10,17,37,60,68,116,178,204],"practitioners.":[11],"For":[12],"the":[13,55,98,127,138,142,160,172],"sake":[14],"of":[15,32,72,87,93],"accessibility":[16],"resource":[18],"reuse,":[19],"it":[20],"is":[21,40,49,58,213],"important":[22],"to":[23,29,45],"focus":[24],"on":[25,69,90],"adapting":[26,171],"these":[27],"a":[30,70,85,91,154,163,190,206],"variety":[31,92],"down-stream":[33],"scenarios.":[34],"An":[35],"interesting":[36],"practical":[38],"paradigm":[39],"online":[41],"test-time":[42,80],"adaptation,":[43],"according":[44],"which":[46,131,158],"training":[47],"data":[48,53],"inaccessible,":[50],"no":[51],"labelled":[52],"from":[54],"test":[56,66,150],"distribution":[57],"available,":[59],"adaptation":[61,81],"can":[62],"only":[63,111],"happen":[64],"at":[65,149,215],"time":[67],"handful":[71],"samples.":[73],"In":[74],"this":[75],"paper,":[76],"we":[77,152],"investigate":[78],"how":[79],"methods":[82],"fare":[83],"number":[86],"pre-trained":[88],"real-world":[94],"scenarios,":[95],"significantly":[96],"extending":[97],"way":[99],"they":[100,108,132],"have":[101,205],"been":[102],"originally":[103],"evaluated.":[104],"We":[105],"show":[106],"that":[107,144],"perform":[109],"well":[110],"in":[112,130],"narrowly-defined":[113],"experimental":[114],"setups":[115],"sometimes":[117],"fail":[118],"catastrophically":[119],"when":[120],"their":[121],"hyperparameters":[122],"are":[123,133],"not":[124],"selected":[125],"same":[128],"scenario":[129],"being":[134,201],"tested.":[135],"Motivated":[136],"by":[137],"inherent":[139],"uncertainty":[140],"around":[141],"conditions":[143],"will":[145],"ultimately":[146],"be":[147],"encountered":[148],"time,":[151],"propose":[153],"particularly":[155],"\"conservative\"":[156],"approach,":[157],"addresses":[159],"problem":[161],"with":[162,182],"Laplacian":[164],"Adjusted":[165],"Maximum-likelihood":[166],"Estimation":[167],"(LAME)":[168],"objective.":[169],"By":[170],"model's":[173],"output":[174],"(not":[175],"its":[176],"parameters),":[177],"solving":[179],"our":[180,187],"objective":[181],"an":[183],"efficient":[184],"concave-convex":[185],"procedure,":[186],"approach":[188],"exhibits":[189],"much":[191,207],"higher":[192],"average":[193],"accuracy":[194],"across":[195],"scenarios":[196],"than":[197],"existing":[198],"methods,":[199],"while":[200],"notably":[202],"faster":[203],"lower":[208],"memory":[209],"footprint.":[210],"The":[211],"code":[212],"available":[214],"https://github.com/fiveai/LAME.":[216]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4313025443","counts_by_year":[{"year":2024,"cited_by_count":40},{"year":2023,"cited_by_count":24},{"year":2022,"cited_by_count":2}],"updated_date":"2025-01-16T12:49:22.364249","created_date":"2023-01-06"}