{"id":"https://openalex.org/W3196865505","doi":"https://doi.org/10.1109/iccv48922.2021.00519","title":"GDP: Stabilized Neural Network Pruning via Gates with Differentiable Polarization","display_name":"GDP: Stabilized Neural Network Pruning via Gates with Differentiable Polarization","publication_year":2021,"publication_date":"2021-10-01","ids":{"openalex":"https://openalex.org/W3196865505","doi":"https://doi.org/10.1109/iccv48922.2021.00519","mag":"3196865505"},"language":"en","primary_location":{"id":"doi:10.1109/iccv48922.2021.00519","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv48922.2021.00519","pdf_url":null,"source":{"id":"https://openalex.org/S4363607764","display_name":"2021 IEEE/CVF International Conference on Computer Vision (ICCV)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},"type":"article","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/A5101789281","display_name":"Yi Guo","orcid":"https://orcid.org/0000-0003-0400-2145"},"institutions":[{"id":"https://openalex.org/I4401726859","display_name":"Kuaishou (China)","ror":"https://ror.org/0258as409","country_code":null,"type":"company","lineage":["https://openalex.org/I4401726859"]}],"countries":[],"is_corresponding":true,"raw_author_name":"Yi Guo","raw_affiliation_strings":["Kuaishou Technology"],"affiliations":[{"raw_affiliation_string":"Kuaishou Technology","institution_ids":["https://openalex.org/I4401726859"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009790177","display_name":"Huan Yuan","orcid":"https://orcid.org/0000-0001-5226-8226"},"institutions":[{"id":"https://openalex.org/I4401726859","display_name":"Kuaishou (China)","ror":"https://ror.org/0258as409","country_code":null,"type":"company","lineage":["https://openalex.org/I4401726859"]}],"countries":[],"is_corresponding":false,"raw_author_name":"Huan Yuan","raw_affiliation_strings":["Kuaishou Technology"],"affiliations":[{"raw_affiliation_string":"Kuaishou Technology","institution_ids":["https://openalex.org/I4401726859"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081629672","display_name":"Jianchao Tan","orcid":"https://orcid.org/0000-0002-9862-2654"},"institutions":[{"id":"https://openalex.org/I4401726859","display_name":"Kuaishou (China)","ror":"https://ror.org/0258as409","country_code":null,"type":"company","lineage":["https://openalex.org/I4401726859"]}],"countries":[],"is_corresponding":false,"raw_author_name":"Jianchao Tan","raw_affiliation_strings":["Kuaishou Technology"],"affiliations":[{"raw_affiliation_string":"Kuaishou Technology","institution_ids":["https://openalex.org/I4401726859"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048522863","display_name":"Zhangyang Wang","orcid":"https://orcid.org/0000-0002-2050-5693"},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhangyang Wang","raw_affiliation_strings":["University of Texas at Austin"],"affiliations":[{"raw_affiliation_string":"University of Texas at Austin","institution_ids":["https://openalex.org/I86519309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002854172","display_name":"Sen Yang","orcid":"https://orcid.org/0000-0003-3222-2268"},"institutions":[{"id":"https://openalex.org/I4401726859","display_name":"Kuaishou (China)","ror":"https://ror.org/0258as409","country_code":null,"type":"company","lineage":["https://openalex.org/I4401726859"]}],"countries":[],"is_corresponding":false,"raw_author_name":"Sen Yang","raw_affiliation_strings":["Kuaishou Technology"],"affiliations":[{"raw_affiliation_string":"Kuaishou Technology","institution_ids":["https://openalex.org/I4401726859"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100626179","display_name":"Ji Liu","orcid":"https://orcid.org/0000-0002-4703-991X"},"institutions":[{"id":"https://openalex.org/I4401726859","display_name":"Kuaishou (China)","ror":"https://ror.org/0258as409","country_code":null,"type":"company","lineage":["https://openalex.org/I4401726859"]}],"countries":[],"is_corresponding":false,"raw_author_name":"Ji Liu","raw_affiliation_strings":["Kuaishou Technology"],"affiliations":[{"raw_affiliation_string":"Kuaishou Technology","institution_ids":["https://openalex.org/I4401726859"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5101789281"],"corresponding_institution_ids":["https://openalex.org/I4401726859"],"apc_list":null,"apc_paid":null,"fwci":3.5558,"has_fulltext":false,"cited_by_count":37,"citation_normalized_percentile":{"value":0.94309469,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"5219","last_page":"5230"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9980999827384949,"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"}},"topics":[{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9980999827384949,"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/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.9976999759674072,"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/T11206","display_name":"Model Reduction and Neural Networks","score":0.9769999980926514,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/differentiable-function","display_name":"Differentiable function","score":0.7400351166725159},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6489436030387878},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.5783993005752563},{"id":"https://openalex.org/keywords/polarization","display_name":"Polarization (electrochemistry)","score":0.5237320065498352},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5162398815155029},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38334596157073975},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3331126570701599},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.302465558052063},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.23497465252876282},{"id":"https://openalex.org/keywords/pure-mathematics","display_name":"Pure mathematics","score":0.14020442962646484},{"id":"https://openalex.org/keywords/physical-chemistry","display_name":"Physical chemistry","score":0.07329443097114563}],"concepts":[{"id":"https://openalex.org/C202615002","wikidata":"https://www.wikidata.org/wiki/Q783507","display_name":"Differentiable function","level":2,"score":0.7400351166725159},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6489436030387878},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.5783993005752563},{"id":"https://openalex.org/C205049153","wikidata":"https://www.wikidata.org/wiki/Q2698605","display_name":"Polarization (electrochemistry)","level":2,"score":0.5237320065498352},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5162398815155029},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38334596157073975},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3331126570701599},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.302465558052063},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.23497465252876282},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.14020442962646484},{"id":"https://openalex.org/C147789679","wikidata":"https://www.wikidata.org/wiki/Q11372","display_name":"Physical chemistry","level":1,"score":0.07329443097114563},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccv48922.2021.00519","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv48922.2021.00519","pdf_url":null,"source":{"id":"https://openalex.org/S4363607764","display_name":"2021 IEEE/CVF International Conference on Computer Vision (ICCV)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.699999988079071,"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":159,"referenced_works":["https://openalex.org/W1821462560","https://openalex.org/W1836465849","https://openalex.org/W2108598243","https://openalex.org/W2111453803","https://openalex.org/W2119144962","https://openalex.org/W2156387975","https://openalex.org/W2163605009","https://openalex.org/W2164278908","https://openalex.org/W2173564293","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2242818861","https://openalex.org/W2279098554","https://openalex.org/W2284050935","https://openalex.org/W2331128040","https://openalex.org/W2518108298","https://openalex.org/W2531409750","https://openalex.org/W2547875792","https://openalex.org/W2551895583","https://openalex.org/W2553303224","https://openalex.org/W2612445135","https://openalex.org/W2630837129","https://openalex.org/W2731516819","https://openalex.org/W2764043458","https://openalex.org/W2786054724","https://openalex.org/W2787752464","https://openalex.org/W2798170643","https://openalex.org/W2809624076","https://openalex.org/W2810075754","https://openalex.org/W2886851211","https://openalex.org/W2894740066","https://openalex.org/W2945098486","https://openalex.org/W2945908221","https://openalex.org/W2947681860","https://openalex.org/W2947963429","https://openalex.org/W2949941638","https://openalex.org/W2951104886","https://openalex.org/W2951799221","https://openalex.org/W2960155404","https://openalex.org/W2962818002","https://openalex.org/W2962851801","https://openalex.org/W2962861284","https://openalex.org/W2963000224","https://openalex.org/W2963094099","https://openalex.org/W2963122961","https://openalex.org/W2963163009","https://openalex.org/W2963247446","https://openalex.org/W2963263347","https://openalex.org/W2963363373","https://openalex.org/W2963674932","https://openalex.org/W2963685250","https://openalex.org/W2963828549","https://openalex.org/W2963918968","https://openalex.org/W2964001144","https://openalex.org/W2964203871","https://openalex.org/W2964233199","https://openalex.org/W2964266063","https://openalex.org/W2964299589","https://openalex.org/W2964309882","https://openalex.org/W2965862774","https://openalex.org/W2968019134","https://openalex.org/W2970632972","https://openalex.org/W2971229607","https://openalex.org/W2971275988","https://openalex.org/W2974893078","https://openalex.org/W2976540144","https://openalex.org/W2982561504","https://openalex.org/W2984618279","https://openalex.org/W2994749257","https://openalex.org/W2995463996","https://openalex.org/W2997300524","https://openalex.org/W3005692288","https://openalex.org/W3009043942","https://openalex.org/W3028304412","https://openalex.org/W3034251466","https://openalex.org/W3034408420","https://openalex.org/W3034513523","https://openalex.org/W3034644181","https://openalex.org/W3034674511","https://openalex.org/W3034693242","https://openalex.org/W3034714646","https://openalex.org/W3034797615","https://openalex.org/W3034818206","https://openalex.org/W3035147638","https://openalex.org/W3035200909","https://openalex.org/W3035332806","https://openalex.org/W3035377608","https://openalex.org/W3035467254","https://openalex.org/W3035605662","https://openalex.org/W3035755841","https://openalex.org/W3041028268","https://openalex.org/W3046041674","https://openalex.org/W3088399386","https://openalex.org/W3094522247","https://openalex.org/W3094663250","https://openalex.org/W3094786017","https://openalex.org/W3095508601","https://openalex.org/W3102335301","https://openalex.org/W3102982004","https://openalex.org/W3104263540","https://openalex.org/W3109212549","https://openalex.org/W3113920149","https://openalex.org/W3118608800","https://openalex.org/W3121696187","https://openalex.org/W3126019867","https://openalex.org/W3128677498","https://openalex.org/W3133441631","https://openalex.org/W4297775537","https://openalex.org/W6638523607","https://openalex.org/W6638632666","https://openalex.org/W6638667902","https://openalex.org/W6676611517","https://openalex.org/W6677580257","https://openalex.org/W6682889407","https://openalex.org/W6684191040","https://openalex.org/W6684379799","https://openalex.org/W6685444567","https://openalex.org/W6690026940","https://openalex.org/W6695676441","https://openalex.org/W6702130928","https://openalex.org/W6725543821","https://openalex.org/W6726497184","https://openalex.org/W6728184133","https://openalex.org/W6729448088","https://openalex.org/W6729956949","https://openalex.org/W6737664043","https://openalex.org/W6739696289","https://openalex.org/W6740493225","https://openalex.org/W6745148473","https://openalex.org/W6745499552","https://openalex.org/W6748035112","https://openalex.org/W6748163181","https://openalex.org/W6748481559","https://openalex.org/W6750719829","https://openalex.org/W6752515464","https://openalex.org/W6753069482","https://openalex.org/W6753490951","https://openalex.org/W6755034786","https://openalex.org/W6755166560","https://openalex.org/W6763207085","https://openalex.org/W6763381322","https://openalex.org/W6767064347","https://openalex.org/W6767327937","https://openalex.org/W6767534822","https://openalex.org/W6767905742","https://openalex.org/W6771369672","https://openalex.org/W6771852177","https://openalex.org/W6774743274","https://openalex.org/W6779249178","https://openalex.org/W6779487836","https://openalex.org/W6779893256","https://openalex.org/W6781359717","https://openalex.org/W6782768365","https://openalex.org/W6783189819","https://openalex.org/W6783955940","https://openalex.org/W6785012020","https://openalex.org/W6787972765","https://openalex.org/W6788034315","https://openalex.org/W6790510691"],"related_works":["https://openalex.org/W4285277090","https://openalex.org/W4327738859","https://openalex.org/W2051487156","https://openalex.org/W2348722996","https://openalex.org/W2334570605","https://openalex.org/W2073681303","https://openalex.org/W3181683615","https://openalex.org/W4286826125","https://openalex.org/W1633485514","https://openalex.org/W1604739066"],"abstract_inverted_index":{"Model":[0],"compression":[1,23],"techniques":[2],"are":[3,44],"recently":[4],"gaining":[5],"explosive":[6],"attention":[7],"for":[8,13],"obtaining":[9],"efficient":[10],"AI":[11],"models":[12],"various":[14,30,61,215],"real":[15],"time":[16],"applications.":[17],"Channel":[18],"pruning":[19,36,68,223],"is":[20],"one":[21],"important":[22],"strategy,":[24],"and":[25,82,119,201],"widely":[26],"used":[27],"in":[28],"slimming":[29],"DNNs.":[31],"Previous":[32],"gate-based":[33],"or":[34,128],"importance-based":[35],"methods":[37,69],"aim":[38],"to":[39,60,73,121,145,148,189,193,229],"remove":[40],"channels":[41,168],"whose":[42,238],"\"importance\"":[43],"smallest.":[45],"However,":[46],"it":[47],"remains":[48],"unclear":[49],"what":[50],"criteria":[51],"the":[52,79,83,91,123,133,136,181,194,206,211,232],"channel":[53,62,127],"importance":[54],"should":[55],"be":[56,112,170,178],"measured":[57],"on,":[58],"leading":[59],"selection":[63],"heuristics.":[64],"Some":[65],"other":[66,152,174],"sampling-based":[67],"deploy":[70],"sampling":[71],"strategy":[72],"train":[74],"sub-nets,":[75],"which":[76],"often":[77],"causes":[78],"training":[80,134,164,190],"instability":[81],"compressed":[84],"model\u2019s":[85],"degraded":[86],"performance.":[87],"In":[88],"view":[89],"of":[90,125,143,222],"research":[92],"gaps,":[93],"we":[94],"present":[95],"a":[96,141,160,219],"new":[97],"module":[98],"named":[99],"Gates":[100],"with":[101,247],"Differentiable":[102],"Polarization":[103],"(GDP),":[104],"inspired":[105],"by":[106,159],"principled":[107],"optimization":[108],"ideas.":[109],"GDP":[110,208,228],"can":[111,169,177],"plugged":[113],"before":[114],"convolutional":[115],"layers":[116],"without":[117],"bells":[118],"whistles,":[120],"control":[122],"on-and-off":[124],"each":[126],"whole":[129],"layer":[130],"block.":[131],"During":[132],"process,":[135],"polarization":[137],"effect":[138],"will":[139],"drive":[140],"subset":[142],"gates":[144,153,176],"smoothly":[146],"decrease":[147],"exact":[149],"zero,":[150],"while":[151,173],"gradually":[154],"stay":[155],"away":[156],"from":[157],"zero":[158],"large":[161],"margin.":[162],"When":[163],"terminates,":[165],"those":[166],"zero-gated":[167],"painlessly":[171],"removed,":[172],"non-zero":[175],"absorbed":[179],"into":[180],"succeeding":[182],"convolution":[183],"kernel,":[184],"causing":[185],"completely":[186],"no":[187,242],"interruption":[188],"nor":[191],"damage":[192],"trained":[195],"model.":[196],"Experiments":[197],"conducted":[198],"over":[199,248],"CIFAR-10":[200],"ImageNet":[202],"datasets":[203],"show":[204],"that":[205],"proposed":[207],"algorithm":[209],"achieves":[210],"state-of-the-art":[212],"performance":[213,240],"on":[214,231],"benchmark":[216],"DNNs":[217],"at":[218],"broad":[220],"range":[221],"ratios.":[224],"We":[225],"also":[226],"apply":[227],"DeepLabV3Plus-ResNet50":[230],"challenging":[233],"Pascal":[234],"VOC":[235],"segmentation":[236],"task,":[237],"test":[239],"sees":[241],"drop":[243],"(even":[244],"slightly":[245],"improved)":[246],"60%":[249],"FLOPs":[250],"saving.":[251]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":1}],"updated_date":"2026-03-04T09:10:02.777135","created_date":"2025-10-10T00:00:00"}