{"id":"https://openalex.org/W3083389787","doi":"https://doi.org/10.1145/3386263.3407650","title":"A Privacy-Preserving-Oriented DNN Pruning and Mobile Acceleration Framework","display_name":"A Privacy-Preserving-Oriented DNN Pruning and Mobile Acceleration Framework","publication_year":2020,"publication_date":"2020-09-04","ids":{"openalex":"https://openalex.org/W3083389787","doi":"https://doi.org/10.1145/3386263.3407650","mag":"3083389787"},"language":"en","primary_location":{"id":"doi:10.1145/3386263.3407650","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3386263.3407650","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 on Great Lakes Symposium on VLSI","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/A5101928537","display_name":"Yifan Gong","orcid":"https://orcid.org/0000-0002-3912-097X"},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yifan Gong","raw_affiliation_strings":["Northeastern University, Boston, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University, Boston, MA, USA","institution_ids":["https://openalex.org/I12912129"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037655503","display_name":"Zheng Zhan","orcid":"https://orcid.org/0000-0002-3882-5484"},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zheng Zhan","raw_affiliation_strings":["Northeastern University, Boston, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University, Boston, MA, USA","institution_ids":["https://openalex.org/I12912129"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009375033","display_name":"Zhengang Li","orcid":"https://orcid.org/0009-0001-9920-6716"},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhengang Li","raw_affiliation_strings":["Northeastern University, Boston, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University, Boston, MA, USA","institution_ids":["https://openalex.org/I12912129"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043054935","display_name":"Wei Niu","orcid":"https://orcid.org/0000-0002-2697-7042"},"institutions":[{"id":"https://openalex.org/I16285277","display_name":"William & Mary","ror":"https://ror.org/03hsf0573","country_code":"US","type":"education","lineage":["https://openalex.org/I16285277"]},{"id":"https://openalex.org/I267592682","display_name":"Williams (United States)","ror":"https://ror.org/007zhvp17","country_code":"US","type":"company","lineage":["https://openalex.org/I267592682"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wei Niu","raw_affiliation_strings":["The College of William and Mary, Williamsburg, VA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The College of William and Mary, Williamsburg, VA, USA","institution_ids":["https://openalex.org/I16285277","https://openalex.org/I267592682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016070401","display_name":"Xiaolong Ma","orcid":"https://orcid.org/0000-0003-3753-7648"},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaolong Ma","raw_affiliation_strings":["Northeastern University, Boston, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University, Boston, MA, USA","institution_ids":["https://openalex.org/I12912129"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100390307","display_name":"Wenhao Wang","orcid":"https://orcid.org/0000-0001-7566-2322"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wenhao Wang","raw_affiliation_strings":["University of Illinois at Chicago, Chicago, IL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Illinois at Chicago, Chicago, IL, USA","institution_ids":["https://openalex.org/I39422238"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058025888","display_name":"Bin Ren","orcid":"https://orcid.org/0000-0002-4116-5237"},"institutions":[{"id":"https://openalex.org/I16285277","display_name":"William & Mary","ror":"https://ror.org/03hsf0573","country_code":"US","type":"education","lineage":["https://openalex.org/I16285277"]},{"id":"https://openalex.org/I267592682","display_name":"Williams (United States)","ror":"https://ror.org/007zhvp17","country_code":"US","type":"company","lineage":["https://openalex.org/I267592682"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bin Ren","raw_affiliation_strings":["The College of William and Mary, Williamsburg, VA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The College of William and Mary, Williamsburg, VA, USA","institution_ids":["https://openalex.org/I16285277","https://openalex.org/I267592682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030060072","display_name":"Caiwen Ding","orcid":"https://orcid.org/0000-0003-0891-1231"},"institutions":[{"id":"https://openalex.org/I140172145","display_name":"University of Connecticut","ror":"https://ror.org/02der9h97","country_code":"US","type":"education","lineage":["https://openalex.org/I140172145"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Caiwen Ding","raw_affiliation_strings":["University of Connecticut, Storrs, CT, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Connecticut, Storrs, CT, USA","institution_ids":["https://openalex.org/I140172145"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043582832","display_name":"Xue Lin","orcid":"https://orcid.org/0000-0001-6210-8883"},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xue Lin","raw_affiliation_strings":["Northeastern University, Boston, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University, Boston, MA, USA","institution_ids":["https://openalex.org/I12912129"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054462808","display_name":"Xiaolin Xu","orcid":"https://orcid.org/0000-0001-8393-2783"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaolin Xu","raw_affiliation_strings":["University of Illinois at Chicago, Boston, IL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Illinois at Chicago, Boston, IL, USA","institution_ids":["https://openalex.org/I39422238"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100651384","display_name":"Yanzhi Wang","orcid":"https://orcid.org/0000-0002-3024-7990"},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yanzhi Wang","raw_affiliation_strings":["Northeastern University, Boston, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University, Boston, MA, USA","institution_ids":["https://openalex.org/I12912129"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"119","last_page":"124"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998000264167786,"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":0.9998000264167786,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9930999875068665,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9879999756813049,"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/pruning","display_name":"Pruning","score":0.8710708618164062},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8433668613433838},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.7257196307182312},{"id":"https://openalex.org/keywords/mobile-device","display_name":"Mobile device","score":0.5885942578315735},{"id":"https://openalex.org/keywords/compiler","display_name":"Compiler","score":0.5844562649726868},{"id":"https://openalex.org/keywords/acceleration","display_name":"Acceleration","score":0.5411040782928467},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5354675650596619},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.4979102611541748},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.49439311027526855},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4695330858230591},{"id":"https://openalex.org/keywords/edge-computing","display_name":"Edge computing","score":0.44741290807724},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42450425028800964},{"id":"https://openalex.org/keywords/mobile-edge-computing","display_name":"Mobile edge computing","score":0.41625961661338806},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.407074898481369},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.4061514735221863},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.2426060140132904}],"concepts":[{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.8710708618164062},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8433668613433838},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.7257196307182312},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.5885942578315735},{"id":"https://openalex.org/C169590947","wikidata":"https://www.wikidata.org/wiki/Q47506","display_name":"Compiler","level":2,"score":0.5844562649726868},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.5411040782928467},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5354675650596619},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.4979102611541748},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.49439311027526855},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4695330858230591},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.44741290807724},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42450425028800964},{"id":"https://openalex.org/C2776061582","wikidata":"https://www.wikidata.org/wiki/Q25325231","display_name":"Mobile edge computing","level":3,"score":0.41625961661338806},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.407074898481369},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.4061514735221863},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.2426060140132904},{"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},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","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/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3386263.3407650","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3386263.3407650","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 on Great Lakes Symposium on VLSI","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5136326524","display_name":null,"funder_award_id":"CCF-1919117, CCF-1937500, CNS-1909172","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W2027851979","https://openalex.org/W2158158791","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2515385951","https://openalex.org/W2544902556","https://openalex.org/W2608764892","https://openalex.org/W2618305643","https://openalex.org/W2748428003","https://openalex.org/W2788852320","https://openalex.org/W2791618499","https://openalex.org/W2798170643","https://openalex.org/W2804032941","https://openalex.org/W2807830168","https://openalex.org/W2886851211","https://openalex.org/W2891561769","https://openalex.org/W2891967877","https://openalex.org/W2951569836","https://openalex.org/W2962818002","https://openalex.org/W2962851801","https://openalex.org/W2963000224","https://openalex.org/W2963452728","https://openalex.org/W2963674932","https://openalex.org/W2963694111","https://openalex.org/W2964217848","https://openalex.org/W2964266063","https://openalex.org/W2972731620","https://openalex.org/W4292363360","https://openalex.org/W6687483927","https://openalex.org/W6725543821","https://openalex.org/W6726275242","https://openalex.org/W6755843862"],"related_works":["https://openalex.org/W2778498407","https://openalex.org/W4361251304","https://openalex.org/W3024547383","https://openalex.org/W4210813012","https://openalex.org/W3174690704","https://openalex.org/W2968424451","https://openalex.org/W4221092438","https://openalex.org/W4385335479","https://openalex.org/W2905685817","https://openalex.org/W2730940305"],"abstract_inverted_index":{"Weight":[0],"pruning":[1,24,51,75,93,127],"of":[2,18,40,68,83],"deep":[3],"neural":[4],"networks":[5],"(DNNs)":[6],"has":[7],"been":[8],"proposed":[9,70,120,142],"to":[10,88,158],"satisfy":[11],"the":[12,30,38,60,65,69,79,91,108,119,125,141],"limited":[13],"storage":[14],"and":[15,52,131,153,161],"computing":[16],"capability":[17],"mobile":[19,53],"edge":[20],"devices.":[21,117],"However,":[22],"previous":[23],"methods":[25],"mainly":[26],"focus":[27],"on":[28,78,116],"reducing":[29],"model":[31],"size":[32],"and/or":[33],"improving":[34],"performance":[35],"without":[36],"considering":[37],"privacy":[39],"user":[41],"data.":[42,102],"To":[43],"mitigate":[44],"this":[45],"concern,":[46],"we":[47],"propose":[48],"a":[49,72],"privacy-preserving-oriented":[50],"acceleration":[54],"framework":[55,143],"that":[56,140],"does":[57],"not":[58],"require":[59],"private":[61],"training":[62],"dataset.":[63],"At":[64],"algorithm":[66],"level":[67,110],"framework,":[71,121],"systematic":[73],"weight":[74],"technique":[76],"based":[77],"alternating":[80],"direction":[81],"method":[82],"multipliers":[84],"(ADMM)":[85],"is":[86],"designed":[87],"iteratively":[89],"solve":[90],"pattern-based":[92],"problem":[94],"for":[95,113,129],"each":[96],"layer":[97],"with":[98,155,164],"randomly":[99],"generated":[100],"synthetic":[101],"In":[103],"addition,":[104],"corresponding":[105],"optimizations":[106],"at":[107],"compiler":[109],"are":[111],"leveraged":[112],"inference":[114],"accelerations":[115],"With":[118],"users":[122],"could":[123],"avoid":[124],"time-consuming":[126],"process":[128],"non-experts":[130],"directly":[132],"benefit":[133],"from":[134],"compressed":[135],"models.":[136],"Experimental":[137],"results":[138],"show":[139],"outperforms":[144],"three":[145],"state-of-art":[146],"end-to-end":[147],"DNN":[148],"frameworks,":[149],"i.e.,":[150],"TensorFlow-Lite,":[151],"TVM,":[152],"MNN,":[154],"speedup":[156],"up":[157],"4.2\u00d7,":[159],"2.5\u00d7,":[160],"2.0\u00d7,":[162],"respectively,":[163],"almost":[165],"no":[166],"accuracy":[167],"loss,":[168],"while":[169],"preserving":[170],"data":[171],"privacy.":[172]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
