{"id":"https://openalex.org/W4386825386","doi":"https://doi.org/10.1109/mm.2023.3316433","title":"Reg-TuneV2: A Hardware-Aware and Multiobjective Regression-Based Fine-Tuning Approach for Deep Neural Networks on Embedded Platforms","display_name":"Reg-TuneV2: A Hardware-Aware and Multiobjective Regression-Based Fine-Tuning Approach for Deep Neural Networks on Embedded Platforms","publication_year":2023,"publication_date":"2023-09-18","ids":{"openalex":"https://openalex.org/W4386825386","doi":"https://doi.org/10.1109/mm.2023.3316433"},"language":"en","primary_location":{"id":"doi:10.1109/mm.2023.3316433","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mm.2023.3316433","pdf_url":null,"source":{"id":"https://openalex.org/S59697426","display_name":"IEEE Micro","issn_l":"0272-1732","issn":["0272-1732","1937-4143"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Micro","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://mdsoar.org/bitstreams/b251ca88-b2ac-4ccd-ba4e-1010313b10f8/download","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5007957361","display_name":"Arnab Neelim Mazumder","orcid":"https://orcid.org/0000-0002-9550-7917"},"institutions":[{"id":"https://openalex.org/I79272384","display_name":"University of Maryland, Baltimore County","ror":"https://ror.org/02qskvh78","country_code":"US","type":"education","lineage":["https://openalex.org/I79272384"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Arnab Neelim Mazumder","raw_affiliation_strings":["University of Maryland, Baltimore County, Baltimore, MD, USA"],"affiliations":[{"raw_affiliation_string":"University of Maryland, Baltimore County, Baltimore, MD, USA","institution_ids":["https://openalex.org/I79272384"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084010501","display_name":"Tinoosh Mohsenin","orcid":"https://orcid.org/0000-0001-5551-2124"},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tinoosh Mohsenin","raw_affiliation_strings":["Johns Hopkins University, Baltimore, MD, USA"],"affiliations":[{"raw_affiliation_string":"Johns Hopkins University, Baltimore, MD, USA","institution_ids":["https://openalex.org/I145311948"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5007957361"],"corresponding_institution_ids":["https://openalex.org/I79272384"],"apc_list":null,"apc_paid":null,"fwci":0.4897,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.65657582,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"43","issue":"6","first_page":"74","last_page":"83"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9970999956130981,"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":0.9970999956130981,"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":0.9890999794006348,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9861999750137329,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8572894334793091},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.759048342704773},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.6416592001914978},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.58237624168396},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.563107430934906},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.5081546306610107},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4710139036178589},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.44294852018356323},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.43462860584259033},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.4323657751083374},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.4183615446090698},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40042030811309814},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.12346082925796509}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8572894334793091},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.759048342704773},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.6416592001914978},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.58237624168396},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.563107430934906},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.5081546306610107},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4710139036178589},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.44294852018356323},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.43462860584259033},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.4323657751083374},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.4183615446090698},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40042030811309814},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.12346082925796509},{"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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/mm.2023.3316433","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mm.2023.3316433","pdf_url":null,"source":{"id":"https://openalex.org/S59697426","display_name":"IEEE Micro","issn_l":"0272-1732","issn":["0272-1732","1937-4143"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Micro","raw_type":"journal-article"},{"id":"pmh:oai:mdsoar.org:11603/30012","is_oa":true,"landing_page_url":"http://hdl.handle.net/11603/30012","pdf_url":"https://mdsoar.org/bitstreams/b251ca88-b2ac-4ccd-ba4e-1010313b10f8/download","source":{"id":"https://openalex.org/S4306402556","display_name":"Maryland Shared Open Access Repository (USMAI Consortium)","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":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"},{"id":"doi:10.13016/m25q3u-ir7w","is_oa":true,"landing_page_url":"https://doi.org/10.13016/m25q3u-ir7w","pdf_url":null,"source":{"id":"https://openalex.org/S4306402644","display_name":"Digital Repository at the University of Maryland (University of Maryland College Park)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I66946132","host_organization_name":"University of Maryland, College Park","host_organization_lineage":["https://openalex.org/I66946132"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:mdsoar.org:11603/30012","is_oa":true,"landing_page_url":"http://hdl.handle.net/11603/30012","pdf_url":"https://mdsoar.org/bitstreams/b251ca88-b2ac-4ccd-ba4e-1010313b10f8/download","source":{"id":"https://openalex.org/S4306402556","display_name":"Maryland Shared Open Access Repository (USMAI Consortium)","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":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320309204","display_name":"University of Maryland, Baltimore County","ror":"https://ror.org/02qskvh78"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4386825386.pdf","grobid_xml":"https://content.openalex.org/works/W4386825386.grobid-xml"},"referenced_works_count":16,"referenced_works":["https://openalex.org/W2096733369","https://openalex.org/W2769912137","https://openalex.org/W2797583228","https://openalex.org/W2963918968","https://openalex.org/W3008746569","https://openalex.org/W3039202310","https://openalex.org/W3118608800","https://openalex.org/W3200067639","https://openalex.org/W3213541906","https://openalex.org/W4226209055","https://openalex.org/W4242577057","https://openalex.org/W6746451879","https://openalex.org/W6750665317","https://openalex.org/W6780414980","https://openalex.org/W6810670354","https://openalex.org/W6903759691"],"related_works":["https://openalex.org/W96612179","https://openalex.org/W2770234245","https://openalex.org/W2566006169","https://openalex.org/W2987774938","https://openalex.org/W632915154","https://openalex.org/W4229499248","https://openalex.org/W4378874356","https://openalex.org/W2055733372","https://openalex.org/W2369811061","https://openalex.org/W2752178021"],"abstract_inverted_index":{"Fine-tuning":[0],"deep":[1],"neural":[2,19],"networks":[3],"(DNNs)":[4],"for":[5,42,68,94,105,118],"deployment":[6,47,70],"has":[7],"traditionally":[8],"relied":[9],"on":[10,109,123],"computationally":[11],"intensive":[12],"methods":[13],"such":[14],"as":[15],"grid":[16],"searches":[17],"and":[18,51,78,91,120,140,153],"architecture":[20],"searches,":[21],"which":[22],"may":[23],"not":[24],"consider":[25,33],"hardware-aware":[26],"metrics.":[27],"Moreover,":[28],"it":[29],"is":[30],"essential":[31],"to":[32,36,65,88,116],"multiple":[34,73],"objectives":[35],"develop":[37],"a":[38,62,110,136],"range":[39],"of":[40,103],"solutions":[41],"tiny":[43],"machine":[44],"learning":[45,87],"hardware":[46,69],"with":[48,99,149],"real-time":[49],"latency":[50,79],"low":[52],"power":[53],"constraints.":[54],"To":[55],"address":[56],"these":[57],"problems,":[58],"we":[59],"propose":[60],"Reg-TuneV2,":[61],"systematic":[63],"approach":[64,84],"fine-tune":[66],"DNNs":[67],"by":[71],"considering":[72],"objectives,":[74],"including":[75],"accuracy,":[76],"power,":[77],"contours.":[80],"In":[81],"addition,":[82],"this":[83],"uses":[85],"metric":[86],"achieve":[89],"smaller":[90],"better-suited":[92],"configurations":[93],"deployment,":[95],"achieving":[96],"90.5%":[97],"accuracy":[98],"only":[100],"340":[101],"KB":[102],"memory":[104],"keyword":[106],"spotting":[107],"(KWS)":[108],"field-programmable":[111],"gate":[112],"array.":[113],"When":[114],"compared":[115],"baselines":[117],"KWS":[119],"image":[121],"classification":[122],"the":[124,132],"Nvidia":[125],"Jetson":[126],"Nano":[127],"4-GB":[128],"Software":[129],"Development":[130],"Kit,":[131],"proposed":[133],"method":[134],"achieves":[135],"14.5$":[137],"\\times":[138,142,151,155],"$\u00d7":[139,143,152,156],"101.8$":[141],"reduction":[144],"in":[145],"model":[146],"size":[147],"coupled":[148],"2.5$":[150],"5.9$":[154],"better":[157],"inference":[158],"efficiency,":[159],"respectively.":[160]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-12T08:34:05.389933","created_date":"2025-10-10T00:00:00"}
