{"id":"https://openalex.org/W4293102051","doi":"https://doi.org/10.1145/3520126","title":"CAP\u2019NN: A Class-aware Framework for Personalized Neural Network Inference","display_name":"CAP\u2019NN: A Class-aware Framework for Personalized Neural Network Inference","publication_year":2022,"publication_date":"2022-03-21","ids":{"openalex":"https://openalex.org/W4293102051","doi":"https://doi.org/10.1145/3520126"},"language":"en","primary_location":{"id":"doi:10.1145/3520126","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3520126","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3520126","source":{"id":"https://openalex.org/S136160450","display_name":"ACM Transactions on Embedded Computing Systems","issn_l":"1539-9087","issn":["1539-9087","1558-3465"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Embedded Computing Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3520126","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5021040269","display_name":"Maedeh Hemmat","orcid":"https://orcid.org/0000-0002-0085-4589"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Maedeh Hemmat","raw_affiliation_strings":["University of Wisconsin\u2013Madison, Madison, Wisconsin, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Wisconsin\u2013Madison, Madison, Wisconsin, USA","institution_ids":["https://openalex.org/I135310074"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034301665","display_name":"Joshua San Miguel","orcid":"https://orcid.org/0000-0002-6886-7183"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Joshua San Miguel","raw_affiliation_strings":["University of Wisconsin\u2013Madison, Madison, Wisconsin, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Wisconsin\u2013Madison, Madison, Wisconsin, USA","institution_ids":["https://openalex.org/I135310074"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072204999","display_name":"Azadeh Davoodi","orcid":"https://orcid.org/0000-0001-5213-2556"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Azadeh Davoodi","raw_affiliation_strings":["University of Wisconsin\u2013Madison, Madison, Wisconsin, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Wisconsin\u2013Madison, Madison, Wisconsin, USA","institution_ids":["https://openalex.org/I135310074"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I135310074"],"apc_list":null,"apc_paid":null,"fwci":0.2936,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.52615876,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"21","issue":"5","first_page":"1","last_page":"24"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9995999932289124,"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":0.9995999932289124,"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/T12676","display_name":"Machine Learning and ELM","score":0.9987000226974487,"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":0.9973999857902527,"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":0.903657078742981},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.8469212055206299},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.7106871008872986},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.6421669125556946},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6213066577911377},{"id":"https://openalex.org/keywords/cache","display_name":"Cache","score":0.5691388249397278},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.534648597240448},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5339692234992981},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49921441078186035},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4830377995967865},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.4293968975543976},{"id":"https://openalex.org/keywords/network-architecture","display_name":"Network architecture","score":0.4241548180580139},{"id":"https://openalex.org/keywords/reuse","display_name":"Reuse","score":0.4119129776954651},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3589881658554077},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.22241860628128052}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.903657078742981},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.8469212055206299},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7106871008872986},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.6421669125556946},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6213066577911377},{"id":"https://openalex.org/C115537543","wikidata":"https://www.wikidata.org/wiki/Q165596","display_name":"Cache","level":2,"score":0.5691388249397278},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.534648597240448},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5339692234992981},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49921441078186035},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4830377995967865},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.4293968975543976},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.4241548180580139},{"id":"https://openalex.org/C206588197","wikidata":"https://www.wikidata.org/wiki/Q846574","display_name":"Reuse","level":2,"score":0.4119129776954651},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3589881658554077},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.22241860628128052},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"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/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","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/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3520126","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3520126","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3520126","source":{"id":"https://openalex.org/S136160450","display_name":"ACM Transactions on Embedded Computing Systems","issn_l":"1539-9087","issn":["1539-9087","1558-3465"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Embedded Computing Systems","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1145/3520126","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3520126","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3520126","source":{"id":"https://openalex.org/S136160450","display_name":"ACM Transactions on Embedded Computing Systems","issn_l":"1539-9087","issn":["1539-9087","1558-3465"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Embedded Computing Systems","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G977003363","display_name":"SHF: Small: Synthesis of Complex Deep Neural Networks on Distributed Resource-Constrained Devices","funder_award_id":"2006394","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"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4293102051.pdf","grobid_xml":"https://content.openalex.org/works/W4293102051.grobid-xml"},"referenced_works_count":18,"referenced_works":["https://openalex.org/W1581253957","https://openalex.org/W2010202670","https://openalex.org/W2070328746","https://openalex.org/W2094756095","https://openalex.org/W2128163155","https://openalex.org/W2156150815","https://openalex.org/W2606722458","https://openalex.org/W2611289746","https://openalex.org/W2800920215","https://openalex.org/W2908561972","https://openalex.org/W2908625909","https://openalex.org/W2910343334","https://openalex.org/W2917116807","https://openalex.org/W2945969196","https://openalex.org/W2963363373","https://openalex.org/W2964233199","https://openalex.org/W3091783394","https://openalex.org/W4243519499"],"related_works":["https://openalex.org/W17155033","https://openalex.org/W3207760230","https://openalex.org/W1496222301","https://openalex.org/W1590307681","https://openalex.org/W4312814274","https://openalex.org/W4285370786","https://openalex.org/W2296488620","https://openalex.org/W2358353312","https://openalex.org/W2353836703","https://openalex.org/W4205470293"],"abstract_inverted_index":{"We":[0],"propose":[1,88],"a":[2,89,112,160],"framework":[3],"for":[4,106],"Class-aware":[5],"Personalized":[6],"Neural":[7],"Network":[8],"Inference":[9],"(CAP\u2019NN),":[10],"which":[11],"prunes":[12],"an":[13],"already-trained":[14],"neural":[15],"network":[16,98],"model":[17,141],"based":[18,99],"on":[19,100,136],"the":[20,29,58,62,67,77,82,97,101,147,156,163],"preferences":[21],"of":[22,31,80,104,162],"individual":[23],"users.":[24],"Specifically,":[25],"by":[26,151],"adapting":[27],"to":[28,39,44,60,75,116,139,153],"subset":[30,161],"output":[32],"classes":[33,95,165],"that":[34,54,92],"each":[35,107],"user":[36,157],"is":[37,42],"expected":[38],"encounter,":[40],"CAP\u2019NN":[41,64,134],"able":[43],"prune":[45],"not":[46],"only":[47,158],"ineffectual":[48],"neurons":[49,53,105],"but":[50],"also":[51,65],"miseffectual":[52],"confuse":[55],"classification,":[56],"without":[57],"need":[59],"retrain":[61],"network.":[63,83],"exploits":[66],"similarities":[68],"among":[69],"pruning":[70,81],"requests":[71],"from":[72,121],"different":[73],"users":[74],"minimize":[76],"timing":[78],"overheads":[79],"To":[84],"achieve":[85],"this,":[86],"we":[87],"clustering":[90],"algorithm":[91],"groups":[93],"similar":[94],"in":[96,166],"firing":[102],"rates":[103],"class":[108],"and":[109,118,131],"then":[110],"implement":[111],"lightweight":[113],"cache":[114],"architecture":[115],"store":[117],"reuse":[119],"information":[120],"previously":[122],"pruned":[123],"networks.":[124,168],"In":[125],"our":[126],"experiments":[127],"with":[128],"VGG-16,":[129],"AlexNet,":[130],"ResNet-152":[132],"networks,":[133],"achieves,":[135],"average,":[137],"up":[138,152],"47%":[140],"size":[142],"reduction":[143],"while":[144],"actually":[145],"improving":[146],"top-1(5)":[148],"classification":[149],"accuracy":[150],"3.9%(3.4%)":[154],"when":[155],"encounters":[159],"trained":[164],"these":[167]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
