{"id":"https://openalex.org/W3194443621","doi":"https://doi.org/10.1145/3459637.3482230","title":"An Efficient Quantitative Approach for Optimizing Convolutional Neural Networks","display_name":"An Efficient Quantitative Approach for Optimizing Convolutional Neural Networks","publication_year":2021,"publication_date":"2021-10-26","ids":{"openalex":"https://openalex.org/W3194443621","doi":"https://doi.org/10.1145/3459637.3482230","mag":"3194443621"},"language":"en","primary_location":{"id":"doi:10.1145/3459637.3482230","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3459637.3482230","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3459637.3482230","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Information &amp; Knowledge Management","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3459637.3482230","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101589099","display_name":"Yuke Wang","orcid":"https://orcid.org/0000-0002-0360-8738"},"institutions":[{"id":"https://openalex.org/I154570441","display_name":"University of California, Santa Barbara","ror":"https://ror.org/02t274463","country_code":"US","type":"education","lineage":["https://openalex.org/I154570441"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuke Wang","raw_affiliation_strings":["University of California, Santa Barbara, Santa Barbara, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California, Santa Barbara, Santa Barbara, CA, USA","institution_ids":["https://openalex.org/I154570441"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013994586","display_name":"Boyuan Feng","orcid":"https://orcid.org/0000-0002-1975-4027"},"institutions":[{"id":"https://openalex.org/I154570441","display_name":"University of California, Santa Barbara","ror":"https://ror.org/02t274463","country_code":"US","type":"education","lineage":["https://openalex.org/I154570441"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Boyuan Feng","raw_affiliation_strings":["University of California, Santa Barbara, Santa Barbara, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California, Santa Barbara, Santa Barbara, CA, USA","institution_ids":["https://openalex.org/I154570441"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048261129","display_name":"Xueqiao Peng","orcid":"https://orcid.org/0000-0001-8004-393X"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xueqiao Peng","raw_affiliation_strings":["The Ohio State University, Columbus, OH, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Ohio State University, Columbus, OH, USA","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048052285","display_name":"Yufei Ding","orcid":"https://orcid.org/0000-0002-8716-5793"},"institutions":[{"id":"https://openalex.org/I154570441","display_name":"University of California, Santa Barbara","ror":"https://ror.org/02t274463","country_code":"US","type":"education","lineage":["https://openalex.org/I154570441"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yufei Ding","raw_affiliation_strings":["University of California, Santa Barbara, Santa Barbara, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California, Santa Barbara, Santa Barbara, CA, USA","institution_ids":["https://openalex.org/I154570441"]}]}],"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":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2050","last_page":"2059"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":1.0,"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":1.0,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9993000030517578,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9993000030517578,"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":0.8599115610122681},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.8217067718505859},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.6795443296432495},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6297914981842041},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.6100109219551086},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5900712013244629},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.5648953914642334},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5607523322105408},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5231579542160034},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4458438456058502},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.4284776747226715},{"id":"https://openalex.org/keywords/popularity","display_name":"Popularity","score":0.4190897047519684},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3874465525150299},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.3403177559375763},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.2828221321105957},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07802629470825195}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8599115610122681},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8217067718505859},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.6795443296432495},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6297914981842041},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.6100109219551086},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5900712013244629},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.5648953914642334},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5607523322105408},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5231579542160034},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4458438456058502},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.4284776747226715},{"id":"https://openalex.org/C2780586970","wikidata":"https://www.wikidata.org/wiki/Q1357284","display_name":"Popularity","level":2,"score":0.4190897047519684},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3874465525150299},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.3403177559375763},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2828221321105957},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07802629470825195},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3459637.3482230","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3459637.3482230","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3459637.3482230","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Information &amp; Knowledge Management","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2009.05236","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2009.05236","pdf_url":"https://arxiv.org/pdf/2009.05236","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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"}],"best_oa_location":{"id":"doi:10.1145/3459637.3482230","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3459637.3482230","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3459637.3482230","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Information &amp; Knowledge Management","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.6000000238418579}],"awards":[{"id":"https://openalex.org/G1105249996","display_name":null,"funder_award_id":"DMR 1720256","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G1237365475","display_name":null,"funder_award_id":"DMR 1720256","funder_id":"https://openalex.org/F4320337367","funder_display_name":"Division of Materials Research"},{"id":"https://openalex.org/G1875027798","display_name":null,"funder_award_id":"MRSEC; NSF DMR 1720256","funder_id":"https://openalex.org/F4320337965","funder_display_name":"California NanoSystems Institute"},{"id":"https://openalex.org/G2045646697","display_name":null,"funder_award_id":"DMR 1720256","funder_id":"https://openalex.org/F4320333422","funder_display_name":"Materials Research Science and Engineering Center, Harvard University"},{"id":"https://openalex.org/G3282081486","display_name":null,"funder_award_id":"NSF DMR 1720256","funder_id":"https://openalex.org/F4320333422","funder_display_name":"Materials Research Science and Engineering Center, Harvard University"},{"id":"https://openalex.org/G4228342300","display_name":null,"funder_award_id":"NSF DMR 1720256","funder_id":"https://openalex.org/F4320332500","funder_display_name":"University of California, Santa Barbara"},{"id":"https://openalex.org/G4250104368","display_name":null,"funder_award_id":"1720256","funder_id":"https://openalex.org/F4320337367","funder_display_name":"Division of Materials Research"},{"id":"https://openalex.org/G5009579348","display_name":null,"funder_award_id":"MRSEC; NSF DMR 1720256","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5727775474","display_name":null,"funder_award_id":"MRSEC; NSF DMR 1720256","funder_id":"https://openalex.org/F4320333422","funder_display_name":"Materials Research Science and Engineering Center, Harvard University"},{"id":"https://openalex.org/G6265117655","display_name":null,"funder_award_id":"OAC-1925717","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6512159266","display_name":null,"funder_award_id":"1720256","funder_id":"https://openalex.org/F4320333422","funder_display_name":"Materials Research Science and Engineering Center, Harvard University"},{"id":"https://openalex.org/G6912258823","display_name":"Materials Research Science and Engineering Center at UCSB","funder_award_id":"1720256","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7061003935","display_name":null,"funder_award_id":"NSF DMR 1720256","funder_id":"https://openalex.org/F4320337965","funder_display_name":"California NanoSystems Institute"},{"id":"https://openalex.org/G7437795455","display_name":null,"funder_award_id":"1720256","funder_id":"https://openalex.org/F4320332500","funder_display_name":"University of California, Santa Barbara"},{"id":"https://openalex.org/G8230913862","display_name":null,"funder_award_id":"NSF DMR 1720256","funder_id":"https://openalex.org/F4320337367","funder_display_name":"Division of Materials Research"},{"id":"https://openalex.org/G8933114764","display_name":null,"funder_award_id":"NSF DMR 1720256","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"},{"id":"https://openalex.org/F4320322725","display_name":"China Scholarship Council","ror":"https://ror.org/04atp4p48"},{"id":"https://openalex.org/F4320332500","display_name":"University of California, Santa Barbara","ror":"https://ror.org/02t274463"},{"id":"https://openalex.org/F4320333422","display_name":"Materials Research Science and Engineering Center, Harvard University","ror":null},{"id":"https://openalex.org/F4320337367","display_name":"Division of Materials Research","ror":"https://ror.org/01pc7k308"},{"id":"https://openalex.org/F4320337965","display_name":"California NanoSystems Institute","ror":"https://ror.org/00q7fqf35"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3194443621.pdf","grobid_xml":"https://content.openalex.org/works/W3194443621.grobid-xml"},"referenced_works_count":45,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1903029394","https://openalex.org/W2016053056","https://openalex.org/W2102605133","https://openalex.org/W2108598243","https://openalex.org/W2109970490","https://openalex.org/W2113325037","https://openalex.org/W2118097920","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2274287116","https://openalex.org/W2515385951","https://openalex.org/W2531409750","https://openalex.org/W2549139847","https://openalex.org/W2556833785","https://openalex.org/W2594529350","https://openalex.org/W2612445135","https://openalex.org/W2748428003","https://openalex.org/W2769653148","https://openalex.org/W2785366763","https://openalex.org/W2883780447","https://openalex.org/W2949264490","https://openalex.org/W2951104886","https://openalex.org/W2951886768","https://openalex.org/W2962746461","https://openalex.org/W2962835968","https://openalex.org/W2962851801","https://openalex.org/W2962890454","https://openalex.org/W2962965870","https://openalex.org/W2963125010","https://openalex.org/W2963163009","https://openalex.org/W2963821229","https://openalex.org/W2964081807","https://openalex.org/W2964331719","https://openalex.org/W2964350391","https://openalex.org/W2965658867","https://openalex.org/W2994985593","https://openalex.org/W2995999070","https://openalex.org/W2997365222","https://openalex.org/W2998003319","https://openalex.org/W3118608800","https://openalex.org/W4295185264","https://openalex.org/W4297775537","https://openalex.org/W4300687870","https://openalex.org/W4308909683"],"related_works":["https://openalex.org/W2368605798","https://openalex.org/W17155033","https://openalex.org/W2518037665","https://openalex.org/W2348524959","https://openalex.org/W2477036161","https://openalex.org/W3207760230","https://openalex.org/W2368049389","https://openalex.org/W1496222301","https://openalex.org/W2384861574","https://openalex.org/W4294565801"],"abstract_inverted_index":{"With":[0],"the":[1,36,42,93,103],"increasing":[2],"popularity":[3],"of":[4,31,44,50,72,76],"deep":[5],"learning,":[6],"Convolutional":[7],"Neural":[8],"Networks":[9],"(CNNs)":[10],"have":[11,55],"been":[12,56],"widely":[13],"applied":[14],"in":[15,29,92],"various":[16],"domains,":[17],"such":[18],"as":[19],"image":[20],"classification":[21],"and":[22,25,52],"object":[23],"detection,":[24],"achieve":[26],"stunning":[27],"success":[28],"terms":[30],"their":[32],"high":[33],"accuracy":[34,79],"over":[35],"traditional":[37],"statistical":[38],"methods.":[39],"To":[40],"exploit":[41],"potentials":[43],"CNN":[45,64],"models,":[46],"a":[47],"huge":[48],"amount":[49],"research":[51],"industry":[53],"efforts":[54],"devoted":[57],"to":[58,101],"optimizing":[59],"CNNs.":[60],"Among":[61],"these":[62],"endeavors,":[63],"architecture":[65],"design":[66],"has":[67],"attracted":[68],"tremendous":[69],"attention":[70],"because":[71],"its":[73],"great":[74],"potential":[75],"improving":[77],"model":[78,82],"or":[80,96],"reducing":[81],"complexity.":[83],"However,":[84],"existing":[85],"work":[86],"either":[87],"introduces":[88],"repeated":[89],"training":[90],"overhead":[91],"search":[94],"process":[95],"lacks":[97],"an":[98],"interpretable":[99],"metric":[100],"guide":[102],"design.":[104]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2021-08-30T00:00:00"}
