{"id":"https://openalex.org/W3000865935","doi":"https://doi.org/10.48550/arxiv.2001.08839","title":"SS-Auto: A Single-Shot, Automatic Structured Weight Pruning Framework of DNNs with Ultra-High Efficiency","display_name":"SS-Auto: A Single-Shot, Automatic Structured Weight Pruning Framework of DNNs with Ultra-High Efficiency","publication_year":2020,"publication_date":"2020-01-23","ids":{"openalex":"https://openalex.org/W3000865935","doi":"https://doi.org/10.48550/arxiv.2001.08839","mag":"3000865935"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2001.08839","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2001.08839","pdf_url":"https://arxiv.org/pdf/2001.08839","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2001.08839","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101633365","display_name":"Zhengang Li","orcid":"https://orcid.org/0000-0001-6644-4761","observed_orcids":["https://orcid.org/0000-0001-6644-4761"]},"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":"Li, Zhengang","raw_affiliation_strings":["Northeastern University ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University ,","institution_ids":["https://openalex.org/I12912129"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Gong, Yifan","orcid":null,"observed_orcids":[]},"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":"Gong, Yifan","raw_affiliation_strings":["Northeastern University ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University ,","institution_ids":["https://openalex.org/I12912129"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016070401","display_name":"Xiaolong Ma","orcid":"https://orcid.org/0000-0003-3753-7648","observed_orcids":["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":"Ma, Xiaolong","raw_affiliation_strings":["Northeastern University ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University ,","institution_ids":["https://openalex.org/I12912129"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100321843","display_name":"Sijia Liu","orcid":"https://orcid.org/0000-0003-2817-6991","observed_orcids":["https://orcid.org/0000-0003-2817-6991","https://orcid.org/0009-0003-8538-9528"]},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Liu, Sijia","raw_affiliation_strings":["IBM Watson Lab 1 {li "],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Watson Lab 1 {li ","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083232044","display_name":"Mengshu Sun","orcid":"https://orcid.org/0000-0003-3540-1464","observed_orcids":["https://orcid.org/0000-0003-3540-1464"]},"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":"Sun, Mengshu","raw_affiliation_strings":["Northeastern University ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University ,","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","observed_orcids":["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":"Zhan, Zheng","raw_affiliation_strings":["Northeastern University ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University ,","institution_ids":["https://openalex.org/I12912129"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078971265","display_name":"Zhenglun Kong","orcid":"https://orcid.org/0000-0002-8120-4456","observed_orcids":["https://orcid.org/0000-0002-8120-4456"]},"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":"Kong, Zhenglun","raw_affiliation_strings":["Northeastern University ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University ,","institution_ids":["https://openalex.org/I12912129"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007300551","display_name":"Geng Yuan","orcid":"https://orcid.org/0000-0001-9844-992X","observed_orcids":["https://orcid.org/0000-0001-9844-992X"]},"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":"Yuan, Geng","raw_affiliation_strings":["Northeastern University ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University ,","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","observed_orcids":["https://orcid.org/0000-0002-3024-7990","https://orcid.org/0009-0009-3924-6466","https://orcid.org/0009-0008-4749-5860"]},"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":"Wang, Yanzhi","raw_affiliation_strings":["Northeastern University ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University ,","institution_ids":["https://openalex.org/I12912129"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":19,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9994999766349792,"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":0.9994999766349792,"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/T12535","display_name":"Machine Learning and Data Classification","score":9.999999747378752e-05,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.0,"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/deep-neural-network-compression","display_name":"deep neural network compression","score":0.7680000066757202},{"id":"https://openalex.org/keywords/l0-norm-sparsity","display_name":"l0-norm sparsity","score":0.7799999713897705},{"id":"https://openalex.org/keywords/alternating-direction-method-of-multipliers","display_name":"alternating direction method of multipliers","score":0.890999972820282},{"id":"https://openalex.org/keywords/model-compression","display_name":"model compression","score":0.414000004529953},{"id":"https://openalex.org/keywords/inference-acceleration","display_name":"inference acceleration","score":0.7820000052452087},{"id":"https://openalex.org/keywords/smartphone-deployment","display_name":"smartphone deployment","score":0.597000002861023}],"concepts":[{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.8079462051391602},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6957722306251526},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6799917221069336},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.6537094116210938},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4753936529159546},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.4509834051132202},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.4327058792114258},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35406941175460815},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34855568408966064},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.13937464356422424},{"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2001.08839","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2001.08839","pdf_url":"https://arxiv.org/pdf/2001.08839","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2001.08839","doi":"https://doi.org/10.48550/arxiv.2001.08839","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2001.08839","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2001.08839","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2001.08839","pdf_url":"https://arxiv.org/pdf/2001.08839","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3000865935.pdf","grobid_xml":"https://content.openalex.org/works/W3000865935.grobid-xml"},"referenced_works_count":29,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W2160815625","https://openalex.org/W2163605009","https://openalex.org/W2164278908","https://openalex.org/W2194775991","https://openalex.org/W2285660444","https://openalex.org/W2295652899","https://openalex.org/W2507318699","https://openalex.org/W2513419314","https://openalex.org/W2515385951","https://openalex.org/W2525778437","https://openalex.org/W2553303224","https://openalex.org/W2594529350","https://openalex.org/W2756085244","https://openalex.org/W2788852320","https://openalex.org/W2807830168","https://openalex.org/W2884180697","https://openalex.org/W2886851211","https://openalex.org/W2891561769","https://openalex.org/W2896409484","https://openalex.org/W2913535645","https://openalex.org/W2924498682","https://openalex.org/W2955856103","https://openalex.org/W2962818002","https://openalex.org/W2963094099","https://openalex.org/W2963674932","https://openalex.org/W2964266063","https://openalex.org/W3013407975","https://openalex.org/W3139203094"],"related_works":["https://openalex.org/W2997768846","https://openalex.org/W2924498682","https://openalex.org/W3130875094","https://openalex.org/W2884180697","https://openalex.org/W3184314443","https://openalex.org/W4312929503","https://openalex.org/W3212348580","https://openalex.org/W4391257658","https://openalex.org/W4412462821","https://openalex.org/W2788852320"],"abstract_inverted_index":{"Structured":[0],"weight":[1],"pruning":[2,35,54,60,63,128],"is":[3,98],"a":[4,50,95],"representative":[5],"model":[6],"compression":[7],"technique":[8],"of":[9,32,75,90,104],"DNNs":[10],"for":[11,25,83],"hardware":[12],"efficiency":[13],"and":[14,41,61,86,117],"inference":[15,135],"accelerations.":[16],"Previous":[17],"works":[18],"in":[19,79],"this":[20],"area":[21],"leave":[22],"great":[23],"space":[24],"improvement":[26],"since":[27],"sparse":[28],"structures":[29],"with":[30],"combinations":[31],"different":[33],"structured":[34,53],"schemes":[36],"are":[37],"not":[38],"exploited":[39],"fully":[40],"efficiently.":[42],"To":[43],"mitigate":[44],"the":[45,72,92,102,111,122,141,148],"limitations,":[46],"we":[47],"propose":[48],"SS-Auto,":[49],"single-shot,":[51],"automatic":[52],"framework":[55,124,143],"that":[56,121],"can":[57,125],"achieve":[58,126],"row":[59],"column":[62],"simultaneously.":[64],"We":[65],"adopt":[66],"soft":[67],"constraint-based":[68],"formulation":[69],"to":[70,100],"alleviate":[71],"strong":[73],"non-convexity":[74],"l0-norm":[76],"constraints":[77],"used":[78],"state-of-the-art":[80],"ADMM-based":[81],"methods":[82],"faster":[84],"convergence":[85],"fewer":[87],"hyperparameters.":[88],"Instead":[89],"solving":[91],"problem":[93],"directly,":[94],"Primal-Proximal":[96],"solution":[97],"proposed":[99,123,142],"avoid":[101],"pitfall":[103],"penalizing":[105],"all":[106],"weights":[107],"equally,":[108],"thereby":[109],"enhancing":[110],"accuracy.":[112,132],"Extensive":[113],"experiments":[114],"on":[115,147],"CIFAR-10":[116],"CIFAR-100":[118],"datasets":[119],"demonstrate":[120],"ultra-high":[127],"rates":[129],"while":[130],"maintaining":[131],"Furthermore,":[133],"significant":[134],"speedup":[136],"has":[137],"been":[138],"observed":[139],"from":[140],"through":[144],"actual":[145],"measurements":[146],"smartphone.":[149]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":1}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2020-01-30T00:00:00"}