{"id":"https://openalex.org/W2962818002","doi":"https://doi.org/10.1145/3297858.3304076","title":"ADMM-NN","display_name":"ADMM-NN","publication_year":2019,"publication_date":"2019-04-04","ids":{"openalex":"https://openalex.org/W2962818002","doi":"https://doi.org/10.1145/3297858.3304076","mag":"2962818002"},"language":"en","primary_location":{"id":"doi:10.1145/3297858.3304076","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3297858.3304076","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3297858.3304076","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Fourth International Conference on Architectural Support for Programming Languages and Operating Systems","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3297858.3304076","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5051490998","display_name":"Ao Ren","orcid":"https://orcid.org/0000-0002-2322-8038"},"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":true,"raw_author_name":"Ao Ren","raw_affiliation_strings":["Northeastern University, Boston, MA, USA"],"affiliations":[{"raw_affiliation_string":"Northeastern University, Boston, MA, USA","institution_ids":["https://openalex.org/I12912129"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101507891","display_name":"Tianyun Zhang","orcid":"https://orcid.org/0000-0002-2475-6414"},"institutions":[{"id":"https://openalex.org/I70983195","display_name":"Syracuse University","ror":"https://ror.org/025r5qe02","country_code":"US","type":"education","lineage":["https://openalex.org/I70983195"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tianyun Zhang","raw_affiliation_strings":["Syracuse University, Syracuse, NY, USA"],"affiliations":[{"raw_affiliation_string":"Syracuse University, Syracuse, NY, USA","institution_ids":["https://openalex.org/I70983195"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010753766","display_name":"Shaokai Ye","orcid":"https://orcid.org/0000-0003-4250-2220"},"institutions":[{"id":"https://openalex.org/I70983195","display_name":"Syracuse University","ror":"https://ror.org/025r5qe02","country_code":"US","type":"education","lineage":["https://openalex.org/I70983195"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shaokai Ye","raw_affiliation_strings":["Syracuse University, Syracuse, NY, USA"],"affiliations":[{"raw_affiliation_string":"Syracuse University, Syracuse, NY, USA","institution_ids":["https://openalex.org/I70983195"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100435411","display_name":"Jiayu Li","orcid":"https://orcid.org/0000-0002-9789-1908"},"institutions":[{"id":"https://openalex.org/I70983195","display_name":"Syracuse University","ror":"https://ror.org/025r5qe02","country_code":"US","type":"education","lineage":["https://openalex.org/I70983195"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiayu Li","raw_affiliation_strings":["Syracuse University, Syracuse, NY, USA"],"affiliations":[{"raw_affiliation_string":"Syracuse University, Syracuse, NY, USA","institution_ids":["https://openalex.org/I70983195"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035679293","display_name":"Wenyao Xu","orcid":"https://orcid.org/0000-0001-6444-9411"},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wenyao Xu","raw_affiliation_strings":["University of Buffalo, SUNY, Buffalo, NY, USA"],"affiliations":[{"raw_affiliation_string":"University of Buffalo, SUNY, Buffalo, NY, USA","institution_ids":["https://openalex.org/I63190737"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047215143","display_name":"Xuehai Qian","orcid":null},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xuehai Qian","raw_affiliation_strings":["University of Southern California, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"University of Southern California, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I1174212"]}]},{"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"],"affiliations":[{"raw_affiliation_string":"Northeastern University, Boston, MA, USA","institution_ids":["https://openalex.org/I12912129"]}]},{"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"],"affiliations":[{"raw_affiliation_string":"Northeastern University, Boston, MA, USA","institution_ids":["https://openalex.org/I12912129"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5051490998"],"corresponding_institution_ids":["https://openalex.org/I12912129"],"apc_list":null,"apc_paid":null,"fwci":24.0683,"has_fulltext":true,"cited_by_count":164,"citation_normalized_percentile":{"value":0.99855599,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"925","last_page":"938"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998000264167786,"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"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9993000030517578,"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/T12676","display_name":"Machine Learning and ELM","score":0.9990000128746033,"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":0.7619476914405823},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.6757838129997253},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.5669246912002563},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5625808835029602},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.45489826798439026},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.4333629012107849},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.42857903242111206},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2332620918750763}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7619476914405823},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.6757838129997253},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.5669246912002563},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5625808835029602},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.45489826798439026},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.4333629012107849},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.42857903242111206},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2332620918750763},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3297858.3304076","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3297858.3304076","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3297858.3304076","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Fourth International Conference on Architectural Support for Programming Languages and Operating Systems","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3297858.3304076","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3297858.3304076","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3297858.3304076","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Fourth International Conference on Architectural Support for Programming Languages and Operating Systems","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.9100000262260437}],"awards":[{"id":"https://openalex.org/G2440810127","display_name":null,"funder_award_id":"1704662","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3793172374","display_name":null,"funder_award_id":"CNS-1717984","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4856824351","display_name":null,"funder_award_id":"1739748","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5004504071","display_name":"CAREER: Algorithm-Centric High Performance Graph Processing","funder_award_id":"1750656","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5195970449","display_name":null,"funder_award_id":"CCF-1733701","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6920192729","display_name":null,"funder_award_id":"CCF-1717754","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7113334034","display_name":null,"funder_award_id":"CCF-1750656","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7116538946","display_name":"AitF: Collaborative Research: A Framework of Simultaneous Acceleration and Storage Reduction on Deep Neural Networks Using Structured Matrices","funder_award_id":"1733701","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7217889279","display_name":null,"funder_award_id":"CNS-1739748","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8222194390","display_name":null,"funder_award_id":"CNS-1704662","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8315138384","display_name":"CSR:  Small:  Collaborative Research:  GAMBIT:  Efficient Graph Processing on a Memristor-based Embedded Computing Platform","funder_award_id":"1717984","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":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2962818002.pdf","grobid_xml":"https://content.openalex.org/works/W2962818002.grobid-xml"},"referenced_works_count":87,"referenced_works":["https://openalex.org/W25321933","https://openalex.org/W569478347","https://openalex.org/W1522301498","https://openalex.org/W1845051632","https://openalex.org/W1902934009","https://openalex.org/W2048266589","https://openalex.org/W2067523571","https://openalex.org/W2108598243","https://openalex.org/W2152839228","https://openalex.org/W2164278908","https://openalex.org/W2194775991","https://openalex.org/W2233116163","https://openalex.org/W2261808795","https://openalex.org/W2267635276","https://openalex.org/W2276486856","https://openalex.org/W2286365479","https://openalex.org/W2289252105","https://openalex.org/W2290132443","https://openalex.org/W2294282016","https://openalex.org/W2475840367","https://openalex.org/W2495112539","https://openalex.org/W2507318699","https://openalex.org/W2510516734","https://openalex.org/W2513419314","https://openalex.org/W2520083297","https://openalex.org/W2554302513","https://openalex.org/W2560017826","https://openalex.org/W2562773490","https://openalex.org/W2563587242","https://openalex.org/W2565125333","https://openalex.org/W2585560244","https://openalex.org/W2585720638","https://openalex.org/W2589646680","https://openalex.org/W2592389822","https://openalex.org/W2593245696","https://openalex.org/W2593390416","https://openalex.org/W2593564159","https://openalex.org/W2594836184","https://openalex.org/W2594928698","https://openalex.org/W2618530766","https://openalex.org/W2619096655","https://openalex.org/W2625457103","https://openalex.org/W2626991402","https://openalex.org/W2657126969","https://openalex.org/W2736953746","https://openalex.org/W2737121650","https://openalex.org/W2739789140","https://openalex.org/W2748818695","https://openalex.org/W2751366252","https://openalex.org/W2754084392","https://openalex.org/W2765815218","https://openalex.org/W2787178869","https://openalex.org/W2790925711","https://openalex.org/W2794478957","https://openalex.org/W2798170643","https://openalex.org/W2899481200","https://openalex.org/W2950248853","https://openalex.org/W2950656546","https://openalex.org/W2951978180","https://openalex.org/W2962835968","https://openalex.org/W2962963202","https://openalex.org/W2963452728","https://openalex.org/W2964299589","https://openalex.org/W2978753875","https://openalex.org/W3047587354","https://openalex.org/W3102169921","https://openalex.org/W3104263540","https://openalex.org/W3104393472","https://openalex.org/W3147929628","https://openalex.org/W4212774754","https://openalex.org/W4212788319","https://openalex.org/W4229779967","https://openalex.org/W4236965008","https://openalex.org/W4240015945","https://openalex.org/W4245199738","https://openalex.org/W4292363360","https://openalex.org/W6600212071","https://openalex.org/W6600248585","https://openalex.org/W6600384961","https://openalex.org/W6600526039","https://openalex.org/W6602021829","https://openalex.org/W6602242674","https://openalex.org/W6602531520","https://openalex.org/W6603957568","https://openalex.org/W6816747942","https://openalex.org/W6819060087","https://openalex.org/W6836035380"],"related_works":["https://openalex.org/W2122678784","https://openalex.org/W1495042958","https://openalex.org/W2282510344","https://openalex.org/W2183994405","https://openalex.org/W3183118997","https://openalex.org/W3214410901","https://openalex.org/W3204400881","https://openalex.org/W3204296682","https://openalex.org/W2917767146","https://openalex.org/W4285609037"],"abstract_inverted_index":{"Model":[0],"compression":[1,27,54,120,234,282],"is":[2,31,113,196,241],"an":[3],"important":[4,49],"technique":[5,181,217],"to":[6,25,32,93,134,153,182,245,272],"facilitate":[7,246],"efficient":[8],"embedded":[9],"and":[10,39,59,109,129,142,205,254,261,265,320,325,348,353,382,387],"hardware":[11,130,144,268,311],"implementations":[12],"of":[13,20,51,70,81,86,97,105,111,170,176,194,201,292,303],"deep":[14],"neural":[15],"networks":[16],"(DNNs),":[17],"a":[18,94,102,179,197,214,290,304],"number":[19,69],"prior":[21],"works":[22],"are":[23,56,372],"dedicated":[24],"model":[26,36,53,99,119,139,233,358],"techniques.":[28],"The":[29,62,191,238,275,335],"target":[30,220],"simultaneously":[33],"reduce":[34],"the":[35,41,65,68,73,76,117,123,143,165,236,258,267,279,287,293,299,333],"storage":[37],"size":[38,140,359],"accelerate":[40],"computation,":[42],"with":[43,187,218],"minor":[44],"effect":[45],"on":[46,323,342,360,366,375],"accuracy.":[47],"Two":[48],"categories":[50],"DNN":[52,98,202,243],"techniques":[55],"weight":[57,60,107,149,203,252,346],"pruning":[58,108,150,204,253,295,301,322,347],"quantization.":[61],"former":[63],"leverages":[64,75],"redundancy":[66,77,87],"in":[67,78,223,229,232,309,356],"weights,":[71],"whereas":[72],"latter":[74,288],"bit":[79],"representation":[80],"weights.":[82],"These":[83],"two":[84,362],"sources":[85],"can":[88,210],"be":[89,135,154,211],"combined,":[90],"thereby":[91,115,227],"leading":[92],"higher":[95,230,331],"degree":[96],"compression.":[100],"However,":[101],"systematic":[103],"framework":[104,169,200],"joint":[106,199],"quantization":[110,206,255],"DNNs":[112,171,378],"lacking,":[114],"limiting":[116],"available":[118],"ratio.":[121],"Moreover,":[122],"computation":[124,259,343],"reduction,":[125,141],"energy":[126,262],"efficiency":[127,263],"improvement,":[128,264],"performance":[131,145,231,269,312],"overhead":[132,146,270],"need":[133],"accounted":[136],"besides":[137],"simply":[138],"resulted":[147],"from":[148],"method":[151],"needs":[152],"taken":[155],"into":[156],"consideration.":[157],"To":[158],"address":[159],"these":[160,361],"limitations,":[161],"we":[162,350],"present":[163],"ADMM-NN,":[164],"first":[166,192,276],"algorithm-hardware":[167],"co-optimization":[168],"using":[172,207],"Alternating":[173],"Direction":[174],"Method":[175],"Multipliers":[177],"(ADMM),":[178],"powerful":[180],"solve":[183],"non-convex":[184],"optimization":[185],"problems":[186],"possibly":[188],"combinatorial":[189],"constraints.":[190],"part":[193,240],"ADMM-NN":[195,317],"systematic,":[198],"ADMM.":[208],"It":[209],"understood":[212],"as":[213,298,380],"smart":[215],"regularization":[216,219],"dynamically":[221],"updated":[222],"each":[224],"ADMM":[225],"iteration,":[226],"resulting":[228],"than":[235,332],"state-of-the-art.":[237,334],"second":[239],"hardware-aware":[242],"optimizations":[244],"hardware-level":[247],"implementations.":[248],"We":[249,384],"perform":[250],"ADMM-based":[251],"considering":[256],"(i)":[257],"reduction":[260],"(ii)":[266],"due":[271],"irregular":[273],"sparsity.":[274],"requirement":[277],"prioritizes":[278],"convolutional":[280],"layer":[281,306],"over":[283],"fully-connected":[284],"layers,":[285],"while":[286],"requires":[289],"concept":[291],"break-even":[294],"ratio,":[296],"defined":[297],"minimum":[300],"ratio":[302],"specific":[305],"that":[307],"results":[308,371],"no":[310],"degradation.":[313],"Without":[314],"accuracy":[315],"loss,":[316],"achieves":[318],"85\u00d7":[319],"24\u00d7":[321],"LeNet-5":[324],"AlexNet":[326],"models,":[327],"respectively,":[328],"---":[329],"significantly":[330],"improvements":[336],"become":[337],"more":[338],"significant":[339],"when":[340,364],"focusing":[341,365],"reduction.":[344],"Combining":[345],"quantization,":[349],"achieve":[351],"1,910\u00d7":[352],"231\u00d7":[354],"reductions":[355],"overall":[357],"benchmarks,":[363],"data":[367],"storage.":[368],"Highly":[369],"promising":[370],"also":[373],"observed":[374],"other":[376],"representative":[377],"such":[379],"VGGNet":[381],"ResNet-50.":[383],"release":[385],"codes":[386],"models":[388],"at":[389],"https://github.com/yeshaokai/admm-nn.":[390]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":16},{"year":2023,"cited_by_count":18},{"year":2022,"cited_by_count":28},{"year":2021,"cited_by_count":41},{"year":2020,"cited_by_count":42},{"year":2019,"cited_by_count":13}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2019-07-30T00:00:00"}
