{"id":"https://openalex.org/W4312525742","doi":"https://doi.org/10.1109/icpr56361.2022.9956511","title":"Learn From the Past: Experience Ensemble Knowledge Distillation","display_name":"Learn From the Past: Experience Ensemble Knowledge Distillation","publication_year":2022,"publication_date":"2022-08-21","ids":{"openalex":"https://openalex.org/W4312525742","doi":"https://doi.org/10.1109/icpr56361.2022.9956511"},"language":"en","primary_location":{"id":"doi:10.1109/icpr56361.2022.9956511","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr56361.2022.9956511","pdf_url":null,"source":{"id":"https://openalex.org/S4363607731","display_name":"2022 26th International Conference on Pattern Recognition (ICPR)","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":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 26th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5052308386","display_name":"Chaofei Wang","orcid":"https://orcid.org/0000-0002-3678-691X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chaofei Wang","raw_affiliation_strings":["Tsinghua University,Department of Automation,Beijing,China","Department of Automation, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,Department of Automation,Beijing,China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100648437","display_name":"Shaowei Zhang","orcid":"https://orcid.org/0000-0002-5973-8785"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaowei Zhang","raw_affiliation_strings":["Tianjin University,School of Microelectronics,Tianjin,China","School of Microelectronics, Tianjin University, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tianjin University,School of Microelectronics,Tianjin,China","institution_ids":["https://openalex.org/I162868743"]},{"raw_affiliation_string":"School of Microelectronics, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101868179","display_name":"Shiji Song","orcid":"https://orcid.org/0000-0003-0858-1770"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shiji Song","raw_affiliation_strings":["Tsinghua University,Department of Automation,Beijing,China","Department of Automation, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,Department of Automation,Beijing,China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013240918","display_name":"Gao Huang","orcid":"https://orcid.org/0000-0002-7251-0988"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gao Huang","raw_affiliation_strings":["Tsinghua University,Department of Automation,Beijing,China","Department of Automation, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,Department of Automation,Beijing,China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.1808,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.81627408,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"4736","last_page":"4743"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9592999815940857,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9592999815940857,"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":0.9399999976158142,"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":0.6464951038360596},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.6394834518432617},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3525177836418152},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.34253203868865967},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.07832121849060059},{"id":"https://openalex.org/keywords/chromatography","display_name":"Chromatography","score":0.07373756170272827}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6464951038360596},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.6394834518432617},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3525177836418152},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.34253203868865967},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.07832121849060059},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.07373756170272827}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr56361.2022.9956511","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr56361.2022.9956511","pdf_url":null,"source":{"id":"https://openalex.org/S4363607731","display_name":"2022 26th International Conference on Pattern Recognition (ICPR)","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":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 26th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.550000011920929}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":73,"referenced_works":["https://openalex.org/W1534477342","https://openalex.org/W1686810756","https://openalex.org/W1690739335","https://openalex.org/W1709548961","https://openalex.org/W1821462560","https://openalex.org/W1996901117","https://openalex.org/W2108598243","https://openalex.org/W2133564696","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2549139847","https://openalex.org/W2561238782","https://openalex.org/W2620998106","https://openalex.org/W2707890836","https://openalex.org/W2739879705","https://openalex.org/W2807912816","https://openalex.org/W2887783173","https://openalex.org/W2936252403","https://openalex.org/W2936864631","https://openalex.org/W2950248853","https://openalex.org/W2951696358","https://openalex.org/W2963125010","https://openalex.org/W2963263347","https://openalex.org/W2963420686","https://openalex.org/W2963446712","https://openalex.org/W2964137095","https://openalex.org/W2981413347","https://openalex.org/W2982242214","https://openalex.org/W2986015886","https://openalex.org/W2992308087","https://openalex.org/W2995607862","https://openalex.org/W2996970889","https://openalex.org/W2997006708","https://openalex.org/W3007079638","https://openalex.org/W3034368386","https://openalex.org/W3034885317","https://openalex.org/W3094502228","https://openalex.org/W3108258117","https://openalex.org/W3118608800","https://openalex.org/W3131861520","https://openalex.org/W3151130473","https://openalex.org/W3170874841","https://openalex.org/W3198054860","https://openalex.org/W3214861801","https://openalex.org/W3215560149","https://openalex.org/W4385245566","https://openalex.org/W6632075054","https://openalex.org/W6637373629","https://openalex.org/W6637551013","https://openalex.org/W6637616945","https://openalex.org/W6638523607","https://openalex.org/W6679434410","https://openalex.org/W6684191040","https://openalex.org/W6684563725","https://openalex.org/W6725739302","https://openalex.org/W6726497184","https://openalex.org/W6730179637","https://openalex.org/W6737496325","https://openalex.org/W6739901393","https://openalex.org/W6739917289","https://openalex.org/W6740474667","https://openalex.org/W6743731764","https://openalex.org/W6769906912","https://openalex.org/W6773604739","https://openalex.org/W6777239595","https://openalex.org/W6779590286","https://openalex.org/W6783658810","https://openalex.org/W6784333009","https://openalex.org/W6787972765","https://openalex.org/W6788135285","https://openalex.org/W6790545024","https://openalex.org/W6804107020","https://openalex.org/W6804324017"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Traditional":[0],"knowledge":[1,18,52,61,66,90,115,161],"distillation":[2,53,67,162,176],"transfers":[3],"\"dark":[4],"knowledge\"":[5],"of":[6,23,74,81,91,114,119,128,180],"a":[7,12,50,71],"pre-trained":[8],"teacher":[9,83],"network":[10],"to":[11,103,107],"student":[13],"network,":[14],"and":[15,86,126,153,164],"ignores":[16],"the":[17,20,24,57,78,82,89,112,123,159,166,173,178],"in":[19,32,111],"training":[21,79,182],"process":[22,80,113],"teacher,":[25],"which":[26],"we":[27,48],"call":[28],"teacher\u2019s":[29,58],"experience.":[30],"However,":[31],"realistic":[33],"educational":[34],"scenarios,":[35],"learning":[36,43],"experience":[37,59,64],"is":[38,101,136],"often":[39],"more":[40],"important":[41],"than":[42],"results.":[44],"In":[45,168],"this":[46],"work,":[47],"propose":[49],"novel":[51],"method":[54],"by":[55,95],"integrating":[56],"for":[60],"transfer,":[62],"named":[63],"ensemble":[65,96,140,175],"(EEKD).":[68],"We":[69],"save":[70],"moderate":[72],"number":[73,127],"intermediate":[75,93,109,129],"models":[76,94,110,130],"from":[77],"model":[84],"uniformly,":[85],"then":[87],"integrate":[88],"these":[92],"technique.":[97],"A":[98,133],"self-attention":[99],"module":[100],"used":[102],"adaptively":[104],"assign":[105],"weights":[106,125],"different":[108],"transfer.":[116],"Three":[117],"principles":[118],"constructing":[120],"EEKD":[121,157,170],"on":[122,151,177],"quality,":[124],"are":[131],"explored.":[132],"surprising":[134],"conclusion":[135],"found":[137],"that":[138,156],"strong":[139,146],"teachers":[141],"do":[142],"not":[143],"necessarily":[144],"produce":[145],"students.":[147],"The":[148],"experimental":[149],"results":[150],"CIFAR-100":[152],"ImageNet":[154],"show":[155],"outperforms":[158],"mainstream":[160],"methods":[163],"achieves":[165],"state-of-the-art.":[167],"particular,":[169],"even":[171],"surpasses":[172],"standard":[174],"premise":[179],"saving":[181],"cost.":[183]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}