{"id":"https://openalex.org/W3205825741","doi":"https://doi.org/10.1145/3474085.3475329","title":"Data-Free Ensemble Knowledge Distillation for Privacy-conscious Multimedia Model Compression","display_name":"Data-Free Ensemble Knowledge Distillation for Privacy-conscious Multimedia Model Compression","publication_year":2021,"publication_date":"2021-10-17","ids":{"openalex":"https://openalex.org/W3205825741","doi":"https://doi.org/10.1145/3474085.3475329","mag":"3205825741"},"language":"en","primary_location":{"id":"doi:10.1145/3474085.3475329","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3474085.3475329","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM International Conference on Multimedia","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/A5101432633","display_name":"Zhiwei Hao","orcid":"https://orcid.org/0000-0001-7869-9139"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiwei Hao","raw_affiliation_strings":["Beijing Institute of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039158745","display_name":"Yong Luo","orcid":"https://orcid.org/0000-0002-2296-6370"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Luo","raw_affiliation_strings":["Wuhan University, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020194895","display_name":"Han Hu","orcid":"https://orcid.org/0000-0001-7532-0496"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Han Hu","raw_affiliation_strings":["Beijing Institute of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044674658","display_name":"Jianping An","orcid":"https://orcid.org/0000-0002-6441-9711"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianping An","raw_affiliation_strings":["Beijing Institute of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041572550","display_name":"Yonggang Wen","orcid":"https://orcid.org/0000-0002-2751-5114"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Yonggang Wen","raw_affiliation_strings":["Nanyang Technological University, Singapore, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore, Singapore","institution_ids":["https://openalex.org/I172675005"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1803","last_page":"1811"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.998199999332428,"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":0.998199999332428,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.998199999332428,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9962000250816345,"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/computer-science","display_name":"Computer science","score":0.8651793003082275},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.6317682266235352},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.5842961668968201},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4937509000301361},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.4892730414867401},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4648723900318146},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.434329628944397},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.4340936839580536},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38857677578926086}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8651793003082275},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.6317682266235352},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.5842961668968201},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4937509000301361},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.4892730414867401},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4648723900318146},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.434329628944397},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.4340936839580536},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38857677578926086},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","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},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3474085.3475329","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3474085.3475329","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1865835052","display_name":"\u591a\u536b\u661f\u73af\u5883\u4e0b\u7684\u81ea\u5b66\u4e60\u6df1\u5ea6\u795e\u7ecf\u7f51\u7edc\u89e3\u8026\u7814\u7a76","funder_award_id":"61971457","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"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":14,"referenced_works":["https://openalex.org/W2115733720","https://openalex.org/W2194775991","https://openalex.org/W2560674852","https://openalex.org/W2620998106","https://openalex.org/W2743289088","https://openalex.org/W2936864631","https://openalex.org/W2963163009","https://openalex.org/W2964137095","https://openalex.org/W2982802130","https://openalex.org/W2986015886","https://openalex.org/W2994742485","https://openalex.org/W2996970889","https://openalex.org/W3034957837","https://openalex.org/W3035460915"],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W2149537132","https://openalex.org/W2018871932","https://openalex.org/W641279757","https://openalex.org/W370975646","https://openalex.org/W1670566515","https://openalex.org/W4242022592","https://openalex.org/W596972243","https://openalex.org/W4313230280","https://openalex.org/W69751022"],"abstract_inverted_index":{"Recent":[0],"advances":[1],"in":[2],"deep":[3],"learning":[4],"bring":[5],"impressive":[6],"performance":[7,90,183],"for":[8],"multimedia":[9],"applications.":[10],"Hence,":[11],"compressing":[12],"and":[13,79,112,144,164],"deploying":[14],"these":[15,92],"applications":[16],"on":[17,170],"resource-limited":[18],"edge":[19],"devices":[20],"via":[21],"model":[22,35,87],"compression":[23,36],"becomes":[24],"attractive.":[25],"Knowledge":[26],"distillation":[27],"(KD)":[28],"is":[29,48],"one":[30],"of":[31,91,123,126,161,199,202],"the":[32,44,76,89,119,124,138,142,152,157,197,203],"most":[33,39],"popular":[34,172],"techniques.":[37],"However,":[38],"well-behaved":[40],"KD":[41,58,73],"approaches":[42],"require":[43],"original":[45],"dataset,":[46],"which":[47,104,134],"usually":[49],"unavailable":[50],"due":[51],"to":[52,136,195],"privacy":[53],"issues,":[54],"while":[55],"existing":[56],"data-free":[57,72],"methods":[59,74],"perform":[60],"much":[61],"worse":[62],"than":[63],"data-required":[64],"counterparts.":[65],"In":[66],"this":[67],"paper,":[68],"we":[69],"analyze":[70],"previous":[71,187],"from":[75],"data":[77],"perspective":[78],"point":[80],"out":[81],"that":[82,178],"using":[83,128],"a":[84,97,106,109,132],"single":[85],"pre-trained":[86,114],"limits":[88],"approaches.":[93],"We":[94,167,189],"then":[95],"propose":[96],"Data-Free":[98],"Ensemble":[99],"knowledge":[100],"Distillation":[101],"(DFED)":[102],"framework,":[103],"contains":[105],"student":[107,120,143],"network,":[108,111],"generator":[110,153],"multiple":[113],"teacher":[115],"networks.":[116],"During":[117],"training,":[118],"mimics":[121],"behaviors":[122],"ensemble":[125],"teachers":[127],"samples":[129,163],"synthesized":[130,162],"by":[131,155],"generator,":[133],"aims":[135],"enlarge":[137],"prediction":[139],"discrepancy":[140],"between":[141,159],"teachers.":[145],"A":[146],"moment":[147],"matching":[148],"loss":[149],"term":[150],"assists":[151],"training":[154],"minimizing":[156],"distance":[158],"activations":[160],"real":[165],"samples.":[166],"evaluate":[168],"DFED":[169],"three":[171],"image":[173],"classification":[174],"datasets.":[175],"Results":[176],"demonstrate":[177],"our":[179],"method":[180],"achieves":[181],"significant":[182],"improvements":[184],"compared":[185],"with":[186],"works.":[188],"also":[190],"design":[191],"an":[192],"ablation":[193],"study":[194],"verify":[196],"effectiveness":[198],"each":[200],"component":[201],"proposed":[204],"framework.":[205]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}