{"id":"https://openalex.org/W7135028721","doi":"https://doi.org/10.1109/tcsi.2026.3667183","title":"AdapSNE: Adaptive Fireworks-Optimized and Entropy-Guided Dataset Sampling for Edge DNN Training","display_name":"AdapSNE: Adaptive Fireworks-Optimized and Entropy-Guided Dataset Sampling for Edge DNN Training","publication_year":2026,"publication_date":"2026-03-12","ids":{"openalex":"https://openalex.org/W7135028721","doi":"https://doi.org/10.1109/tcsi.2026.3667183"},"language":null,"primary_location":{"id":"doi:10.1109/tcsi.2026.3667183","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsi.2026.3667183","pdf_url":null,"source":{"id":"https://openalex.org/S116977442","display_name":"IEEE Transactions on Circuits and Systems I Regular Papers","issn_l":"1549-8328","issn":["1549-8328","1558-0806"],"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 Transactions on Circuits and Systems I: Regular Papers","raw_type":"journal-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":null,"display_name":"Boran Zhao","orcid":"https://orcid.org/0000-0001-5359-1180"},"institutions":[{"id":"https://openalex.org/I4210141742","display_name":"Hybrid Rapeseed Research Center of Shaanxi Province","ror":"https://ror.org/037h5rj68","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210141742"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Boran Zhao","raw_affiliation_strings":["National Key Laboratory of Human-Machine Hybrid Augmented Intelligence, School of Software Engineering, Xi&#x2019;an, Shaanxi, China"],"raw_orcid":"https://orcid.org/0000-0001-5359-1180","affiliations":[{"raw_affiliation_string":"National Key Laboratory of Human-Machine Hybrid Augmented Intelligence, School of Software Engineering, Xi&#x2019;an, Shaanxi, China","institution_ids":["https://openalex.org/I4210141742"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033862586","display_name":"H. Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210141742","display_name":"Hybrid Rapeseed Research Center of Shaanxi Province","ror":"https://ror.org/037h5rj68","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210141742"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hetian Liu","raw_affiliation_strings":["National Key Laboratory of Human-Machine Hybrid Augmented Intelligence, School of Software Engineering, Xi&#x2019;an, Shaanxi, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Key Laboratory of Human-Machine Hybrid Augmented Intelligence, School of Software Engineering, Xi&#x2019;an, Shaanxi, China","institution_ids":["https://openalex.org/I4210141742"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025367177","display_name":"Ze Yuan","orcid":"https://orcid.org/0000-0001-5552-0327"},"institutions":[{"id":"https://openalex.org/I4210141742","display_name":"Hybrid Rapeseed Research Center of Shaanxi Province","ror":"https://ror.org/037h5rj68","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210141742"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zihang Yuan","raw_affiliation_strings":["National Key Laboratory of Human-Machine Hybrid Augmented Intelligence, School of Software Engineering, Xi&#x2019;an, Shaanxi, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Key Laboratory of Human-Machine Hybrid Augmented Intelligence, School of Software Engineering, Xi&#x2019;an, Shaanxi, China","institution_ids":["https://openalex.org/I4210141742"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128850570","display_name":"Li Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Zhu","raw_affiliation_strings":["School of Software Engineering, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, Shaanxi, China"],"raw_orcid":"https://orcid.org/0000-0003-2136-3196","affiliations":[{"raw_affiliation_string":"School of Software Engineering, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, Shaanxi, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128832373","display_name":"Fan Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fan Yang","raw_affiliation_strings":["School of Computer Science and Technology, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, Shaanxi, China"],"raw_orcid":"https://orcid.org/0009-0007-5607-8412","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, Shaanxi, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128902666","display_name":"Lina Xie","orcid":null},"institutions":[{"id":"https://openalex.org/I4210121771","display_name":"First Affiliated Hospital of Xi'an Jiaotong University","ror":"https://ror.org/02tbvhh96","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210121771"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lina Xie","raw_affiliation_strings":["First Affiliated Hospital of Xi&#x2019;an Jiaotong University, Xi&#x2019;an, Shaanxi, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"First Affiliated Hospital of Xi&#x2019;an Jiaotong University, Xi&#x2019;an, Shaanxi, China","institution_ids":["https://openalex.org/I4210121771"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032104477","display_name":"Tian Xia","orcid":"https://orcid.org/0000-0002-2520-3731"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tian Xia","raw_affiliation_strings":["National Key Laboratory of Human-Machine Hybrid Augmented Intelligence, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, Shaanxi, China"],"raw_orcid":"https://orcid.org/0000-0002-2520-3731","affiliations":[{"raw_affiliation_string":"National Key Laboratory of Human-Machine Hybrid Augmented Intelligence, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, Shaanxi, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Wenzhe Zhao","orcid":"https://orcid.org/0000-0002-7001-2125"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenzhe Zhao","raw_affiliation_strings":["National Key Laboratory of Human-Machine Hybrid Augmented Intelligence, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, Shaanxi, China"],"raw_orcid":"https://orcid.org/0000-0002-7001-2125","affiliations":[{"raw_affiliation_string":"National Key Laboratory of Human-Machine Hybrid Augmented Intelligence, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, Shaanxi, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5128912925","display_name":"Pengju Ren","orcid":null},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengju Ren","raw_affiliation_strings":["National Key Laboratory of Human-Machine Hybrid Augmented Intelligence, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, Shaanxi, China"],"raw_orcid":"https://orcid.org/0000-0003-1163-2014","affiliations":[{"raw_affiliation_string":"National Key Laboratory of Human-Machine Hybrid Augmented Intelligence, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, Shaanxi, China","institution_ids":["https://openalex.org/I87445476"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.24138852,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"73","issue":"6","first_page":"4259","last_page":"4270"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.33489999175071716,"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":0.33489999175071716,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.11249999701976776,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.09220000356435776,"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/training","display_name":"Training (meteorology)","score":0.6922000050544739},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5241000056266785},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4860000014305115},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.48510000109672546},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.40209999680519104},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.38440001010894775},{"id":"https://openalex.org/keywords/adaptive-sampling","display_name":"Adaptive sampling","score":0.38029998540878296}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7003999948501587},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.6922000050544739},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5827999711036682},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5241000056266785},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4860000014305115},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.48510000109672546},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.40209999680519104},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.38440001010894775},{"id":"https://openalex.org/C2781395549","wikidata":"https://www.wikidata.org/wiki/Q4680762","display_name":"Adaptive sampling","level":3,"score":0.38029998540878296},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.35519999265670776},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.2987000048160553},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.29580000042915344},{"id":"https://openalex.org/C102248274","wikidata":"https://www.wikidata.org/wiki/Q168388","display_name":"Adaptive filter","level":2,"score":0.2825999855995178},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.2784000039100647},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.2721000015735626},{"id":"https://openalex.org/C2985946229","wikidata":"https://www.wikidata.org/wiki/Q49908","display_name":"Data sampling","level":2,"score":0.2685000002384186},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.26499998569488525},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2599000036716461},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2524000108242035}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcsi.2026.3667183","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsi.2026.3667183","pdf_url":null,"source":{"id":"https://openalex.org/S116977442","display_name":"IEEE Transactions on Circuits and Systems I Regular Papers","issn_l":"1549-8328","issn":["1549-8328","1558-0806"],"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 Transactions on Circuits and Systems I: Regular Papers","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6785566806793213,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[{"id":"https://openalex.org/G1309785897","display_name":null,"funder_award_id":"52441602","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5340218887","display_name":null,"funder_award_id":"62302381","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Training":[0],"deep":[1],"neural":[2],"networks":[3],"(DNNs)":[4],"on":[5],"edge":[6,20],"devices":[7],"faces":[8],"challenges":[9],"due":[10],"to":[11,81,101,108,135],"the":[12,50,68,72,76,82,127,151,189],"large-scale":[13,186],"datasets":[14],"required,":[15],"which":[16,125],"are":[17],"costly":[18],"for":[19,131,142,192],"devices,":[21],"especially":[22],"in":[23,49,116],"large":[24],"language":[25],"model":[26],"(LLM)":[27],"tasks.":[28,194],"To":[29,119,149],"address":[30],"this,":[31],"a":[32],"DNN-free":[33,179],"method":[34,70],"called":[35],"Near-Memory":[36],"Sampling":[37],"(NMS)":[38,180],"has":[39,61],"been":[40],"introduced.":[41],"NMS":[42,60],"reduces":[43],"dimensionality":[44],"and":[45,56,71,99,138,163,178,188],"performs":[46],"exemplar":[47],"sampling":[48],"reduced":[51],"space,":[52],"avoiding":[53],"architectural":[54],"bias":[55],"improving":[57],"generalization.":[58],"However,":[59],"two":[62,105],"limitations:":[63],"1)":[64],"The":[65],"mismatch":[66],"between":[67],"search":[69,134],"non-monotonic":[73,133],"property":[74],"of":[75,84,113,153],"perplexity":[77],"error":[78],"function":[79],"leads":[80],"emergence":[83],"outliers;":[85],"2)":[86],"Key":[87],"parameter":[88],"(<italic":[89],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[90,110],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">i.e.</i>,":[91],"target":[92],"perplexity)":[93],"is":[94],"selected":[95],"empirically,":[96],"introducing":[97],"arbitrariness":[98],"leading":[100],"uneven":[102],"sampling.":[103],"These":[104],"issues":[106],"lead":[107],"<italic":[109],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">representative":[111],"bias</i>":[112],"exemplars,":[114],"resulting":[115],"degraded":[117],"accuracy.":[118],"overcome":[120],"these,":[121],"we":[122,156],"propose":[123],"AdapSNE,":[124],"integrates":[126],"Fireworks":[128],"Algorithm":[129],"(FWA)":[130],"efficient":[132],"avoid":[136],"outliers":[137],"uses":[139],"entropy-guided":[140],"optimization":[141],"uniform":[143],"sampling,":[144],"ensuring":[145],"representative":[146],"training":[147],"samples.":[148],"reduce":[150],"cost":[152],"iterative":[154],"computations,":[155],"design":[157],"an":[158],"accelerator":[159],"with":[160],"custom":[161],"dataflow":[162],"time-multiplexing":[164],"mechanisms.":[165],"Experimental":[166],"results":[167],"show":[168],"that":[169],"AdapSNE":[170],"outperforms":[171],"state-of-the-art":[172],"methods,":[173],"including":[174],"both":[175],"DNN-based":[176],"(DQAS)":[177],"approaches,":[181],"across":[182],"small-scale":[183],"image":[184],"datasets,":[185,187],"MMLU":[190],"benchmark":[191],"LLM":[193]},"counts_by_year":[],"updated_date":"2026-06-02T06:17:35.589633","created_date":"2026-03-13T00:00:00"}