{"id":"https://openalex.org/W3212348580","doi":"https://doi.org/10.1109/dac18074.2021.9586152","title":"A Unified DNN Weight Pruning Framework Using Reweighted Optimization Methods","display_name":"A Unified DNN Weight Pruning Framework Using Reweighted Optimization Methods","publication_year":2021,"publication_date":"2021-11-08","ids":{"openalex":"https://openalex.org/W3212348580","doi":"https://doi.org/10.1109/dac18074.2021.9586152","mag":"3212348580"},"language":"en","primary_location":{"id":"doi:10.1109/dac18074.2021.9586152","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dac18074.2021.9586152","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 58th ACM/IEEE Design Automation Conference (DAC)","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/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, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Syracuse University, USA","institution_ids":["https://openalex.org/I70983195"]}]},{"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, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University, 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, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University, USA","institution_ids":["https://openalex.org/I12912129"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070625162","display_name":"Shanglin Zhou","orcid":"https://orcid.org/0000-0002-6409-7716"},"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":"Shanglin Zhou","raw_affiliation_strings":["University of Connecticut, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Connecticut, USA","institution_ids":["https://openalex.org/I140172145"]}]},{"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, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Connecticut, USA","institution_ids":["https://openalex.org/I140172145"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057639149","display_name":"Makan Fardad","orcid":"https://orcid.org/0000-0003-4643-0535"},"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":"Makan Fardad","raw_affiliation_strings":["Syracuse University, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Syracuse University, USA","institution_ids":["https://openalex.org/I70983195"]}]},{"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, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University, USA","institution_ids":["https://openalex.org/I12912129"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"493","last_page":"498"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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":0.9998999834060669,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9987000226974487,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9979000091552734,"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/regularization","display_name":"Regularization (linguistics)","score":0.7553815841674805},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.7295278310775757},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6677124500274658},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.6536031365394592},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.5473494529724121},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.4782906174659729},{"id":"https://openalex.org/keywords/minification","display_name":"Minification","score":0.45002609491348267},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.44713518023490906},{"id":"https://openalex.org/keywords/bounded-function","display_name":"Bounded function","score":0.4319566786289215},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.40707165002822876},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.36568406224250793},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3477674722671509},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.26085108518600464}],"concepts":[{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.7553815841674805},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.7295278310775757},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6677124500274658},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.6536031365394592},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.5473494529724121},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.4782906174659729},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.45002609491348267},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.44713518023490906},{"id":"https://openalex.org/C34388435","wikidata":"https://www.wikidata.org/wiki/Q2267362","display_name":"Bounded function","level":2,"score":0.4319566786289215},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.40707165002822876},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.36568406224250793},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3477674722671509},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.26085108518600464},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"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/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/dac18074.2021.9586152","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dac18074.2021.9586152","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 58th ACM/IEEE Design Automation Conference (DAC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"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":44,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1667652561","https://openalex.org/W2107861471","https://openalex.org/W2119144962","https://openalex.org/W2138019504","https://openalex.org/W2160815625","https://openalex.org/W2163605009","https://openalex.org/W2164278908","https://openalex.org/W2194775991","https://openalex.org/W2798170643","https://openalex.org/W2806990599","https://openalex.org/W2925035065","https://openalex.org/W2928560789","https://openalex.org/W2945335799","https://openalex.org/W2963000224","https://openalex.org/W2963094099","https://openalex.org/W2963163009","https://openalex.org/W2963674932","https://openalex.org/W2963981420","https://openalex.org/W2964121744","https://openalex.org/W2964299589","https://openalex.org/W2970604398","https://openalex.org/W2970860468","https://openalex.org/W2996019573","https://openalex.org/W2997768846","https://openalex.org/W2998342322","https://openalex.org/W3042215422","https://openalex.org/W3130875094","https://openalex.org/W4288409632","https://openalex.org/W4292363360","https://openalex.org/W4302296459","https://openalex.org/W6631190155","https://openalex.org/W6637151318","https://openalex.org/W6677580257","https://openalex.org/W6684191040","https://openalex.org/W6724998850","https://openalex.org/W6725543821","https://openalex.org/W6750209611","https://openalex.org/W6751913510","https://openalex.org/W6755034786","https://openalex.org/W6760905627","https://openalex.org/W6767036268","https://openalex.org/W6767584280","https://openalex.org/W6790866784"],"related_works":["https://openalex.org/W2373300491","https://openalex.org/W2395294869","https://openalex.org/W2378744544","https://openalex.org/W2594301978","https://openalex.org/W2379704676","https://openalex.org/W1998810860","https://openalex.org/W4206442282","https://openalex.org/W2384505857","https://openalex.org/W2355171581","https://openalex.org/W4220659530"],"abstract_inverted_index":{"To":[0],"address":[1],"the":[2,36,48,57,61,86,93,97,102],"large":[3],"model":[4],"size":[5],"and":[6,21,31,100],"intensive":[7],"computation":[8],"requirement":[9],"of":[10,104],"deep":[11],"neural":[12],"networks":[13],"(DNNs),":[14],"weight":[15,76],"pruning":[16,30,63,77],"techniques":[17],"have":[18],"been":[19],"proposed":[20,90],"generally":[22],"fall":[23],"into":[24],"two":[25],"categories,":[26],"i.e.,":[27],"static":[28],"regularization-based":[29,33],"dynamic":[32],"pruning.":[34],"However,":[35],"former":[37],"method":[38,91],"currently":[39],"suffers":[40],"either":[41],"complex":[42],"workloads":[43],"or":[44],"accuracy":[45,66],"degradation,":[46],"while":[47],"latter":[49],"one":[50],"takes":[51],"a":[52,73],"long":[53],"time":[54,99],"to":[55,59],"tune":[56],"parameters":[58],"achieve":[60],"desired":[62],"rate":[64],"without":[65],"loss.":[67],"In":[68],"this":[69],"paper,":[70],"we":[71],"propose":[72],"unified":[74],"DNN":[75],"framework":[78],"with":[79,107],"dynamically":[80],"updated":[81],"regularization":[82],"terms":[83],"bounded":[84],"by":[85],"designated":[87],"constraint.":[88],"Our":[89],"increases":[92],"compression":[94],"rate,":[95],"reduces":[96,101],"training":[98],"number":[103],"hyper-parameters":[105],"compared":[106],"state-of-the-art":[108],"ADMM-based":[109],"hard":[110],"constraint":[111],"method.":[112]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
