{"id":"https://openalex.org/W2887402482","doi":"https://doi.org/10.1109/hpec.2018.8547604","title":"SlimNets: An Exploration of Deep Model Compression and Acceleration","display_name":"SlimNets: An Exploration of Deep Model Compression and Acceleration","publication_year":2018,"publication_date":"2018-09-01","ids":{"openalex":"https://openalex.org/W2887402482","doi":"https://doi.org/10.1109/hpec.2018.8547604","mag":"2887402482"},"language":"en","primary_location":{"id":"doi:10.1109/hpec.2018.8547604","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hpec.2018.8547604","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE High Performance extreme Computing Conference (HPEC)","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/A5035458544","display_name":"Ini Oguntola","orcid":null},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ini Oguntola","raw_affiliation_strings":["Massachusetts Institute of Technology, Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"Massachusetts Institute of Technology, Cambridge, MA, USA","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020195679","display_name":"Subby Olubeko","orcid":null},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Subby Olubeko","raw_affiliation_strings":["Massachusetts Institute of Technology, Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"Massachusetts Institute of Technology, Cambridge, MA, USA","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002909668","display_name":"Christopher J. Sweeney","orcid":"https://orcid.org/0000-0002-0398-6018"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Christopher Sweeney","raw_affiliation_strings":["Massachusetts Institute of Technology, Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"Massachusetts Institute of Technology, Cambridge, MA, USA","institution_ids":["https://openalex.org/I63966007"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5035458544"],"corresponding_institution_ids":["https://openalex.org/I63966007"],"apc_list":null,"apc_paid":null,"fwci":0.8144,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.79603015,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9986000061035156,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9986000061035156,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9941999912261963,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9915000200271606,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/acceleration","display_name":"Acceleration","score":0.7753231525421143},{"id":"https://openalex.org/keywords/compression","display_name":"Compression (physics)","score":0.5729409456253052},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5570394992828369},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.081065833568573}],"concepts":[{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.7753231525421143},{"id":"https://openalex.org/C180016635","wikidata":"https://www.wikidata.org/wiki/Q2712821","display_name":"Compression (physics)","level":2,"score":0.5729409456253052},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5570394992828369},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.081065833568573},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/hpec.2018.8547604","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hpec.2018.8547604","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE High Performance extreme Computing Conference (HPEC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5,"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1690739335","https://openalex.org/W1799366690","https://openalex.org/W1821462560","https://openalex.org/W2112796928","https://openalex.org/W2114766824","https://openalex.org/W2134797427","https://openalex.org/W2156150815","https://openalex.org/W2163605009","https://openalex.org/W2279221249","https://openalex.org/W2553910756","https://openalex.org/W2751478425","https://openalex.org/W2764043458","https://openalex.org/W2766966408","https://openalex.org/W2963225922","https://openalex.org/W2963674932","https://openalex.org/W2963847166","https://openalex.org/W2964118293","https://openalex.org/W3118608800","https://openalex.org/W4297688279","https://openalex.org/W4297689207","https://openalex.org/W6638523607","https://openalex.org/W6677103964","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2382290278","https://openalex.org/W2478288626","https://openalex.org/W2350741829","https://openalex.org/W2530322880","https://openalex.org/W1596801655"],"abstract_inverted_index":{"Deep":[0],"neural":[1,65],"networks":[2,66],"have":[3],"achieved":[4],"increasingly":[5],"accurate":[6],"results":[7],"on":[8,62,67,119,123,131],"a":[9,52,77,158],"wide":[10],"variety":[11],"of":[12,17,28,33,55,128,171],"complex":[13],"tasks.":[14],"However,":[15],"much":[16],"this":[18],"improvement":[19],"is":[20],"due":[21],"to":[22,57,79],"the":[23,129,138,165,172],"growing":[24],"use":[25,32],"and":[26,50,88,99,108,115,151],"availability":[27],"computational":[29],"resources":[30],"(e.g":[31],"GPUs,":[34],"more":[35,37,94],"layers,":[36],"parameters,":[38],"etc).":[39],"Most":[40],"state-of-the-art":[41],"deep":[42,64,105],"networks,":[43],"despite":[44],"performing":[45],"well,":[46],"over-parameterize":[47],"approximate":[48],"functions":[49],"take":[51],"significant":[53],"amount":[54],"time":[56],"train.":[58],"With":[59],"increased":[60],"focus":[61],"deploying":[63],"resource":[68,86],"constrained":[69],"devices":[70],"like":[71],"smart":[72],"phones,":[73],"there":[74],"has":[75],"been":[76],"push":[78],"evaluate":[80],"why":[81],"these":[82],"models":[83,130],"are":[84,134],"so":[85],"hungry":[87],"how":[89],"they":[90],"can":[91,156],"be":[92],"made":[93],"efficient.":[95],"This":[96],"work":[97],"evaluates":[98],"compares":[100],"three":[101],"distinct":[102],"methods":[103,154],"for":[104],"model":[106],"compression":[107],"acceleration:":[109],"weight":[110],"pruning,":[111],"low":[112],"rank":[113],"factorization,":[114],"knowledge":[116,152],"distillation.":[117],"Comparisons":[118],"VGG":[120],"nets":[121],"trained":[122],"CIFAR10":[124],"show":[125,146],"that":[126,137,147],"each":[127],"their":[132],"own":[133],"effective,":[135],"but":[136],"true":[139],"power":[140],"lies":[141],"in":[142],"combining":[143,149],"them.":[144],"We":[145],"by":[148],"pruning":[150],"distillation":[153],"we":[155],"create":[157],"compressed":[159],"network":[160],"85":[161],"times":[162],"smaller":[163],"than":[164],"original,":[166],"all":[167],"while":[168],"retaining":[169],"96%":[170],"original":[173],"model's":[174],"accuracy.":[175]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
