{"id":"https://openalex.org/W4387344527","doi":"https://doi.org/10.1145/3626100","title":"Enabling Binary Neural Network Training on the Edge","display_name":"Enabling Binary Neural Network Training on the Edge","publication_year":2023,"publication_date":"2023-10-04","ids":{"openalex":"https://openalex.org/W4387344527","doi":"https://doi.org/10.1145/3626100"},"language":"en","primary_location":{"id":"doi:10.1145/3626100","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3626100","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3626100","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/10.1145/3626100","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5013225839","display_name":"Erwei Wang","orcid":"https://orcid.org/0000-0002-3603-6852"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Erwei Wang","raw_affiliation_strings":["Imperial College London, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Imperial College London, United Kingdom","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101557921","display_name":"James J. Davis","orcid":"https://orcid.org/0000-0002-4910-3188"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"James J. Davis","raw_affiliation_strings":["Imperial College London, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Imperial College London, United Kingdom","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103050938","display_name":"Daniele Moro","orcid":"https://orcid.org/0000-0002-5544-830X"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Daniele Moro","raw_affiliation_strings":["Google, United States"],"affiliations":[{"raw_affiliation_string":"Google, United States","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5105672350","display_name":"Piotr Zieli\u0144ski","orcid":"https://orcid.org/0009-0000-1887-496X"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Piotr Zielinski","raw_affiliation_strings":["Google, United States"],"affiliations":[{"raw_affiliation_string":"Google, United States","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080435681","display_name":"Jia Jie Lim","orcid":"https://orcid.org/0009-0002-9383-5324"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jia Jie Lim","raw_affiliation_strings":["iSize, United Kingdom"],"affiliations":[{"raw_affiliation_string":"iSize, United Kingdom","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101732135","display_name":"Claudionor Coelho","orcid":"https://orcid.org/0000-0001-9637-1890"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Claudionor Coelho","raw_affiliation_strings":["Advantest, United States"],"affiliations":[{"raw_affiliation_string":"Advantest, United States","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102897547","display_name":"Satrajit Chatterjee","orcid":"https://orcid.org/0000-0001-8135-8378"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Satrajit Chatterjee","raw_affiliation_strings":["United States"],"affiliations":[{"raw_affiliation_string":"United States","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091532722","display_name":"Peter Y. K. Cheung","orcid":"https://orcid.org/0000-0002-8236-1816"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Peter Y. K. Cheung","raw_affiliation_strings":["Imperial College London, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Imperial College London, United Kingdom","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029829952","display_name":"George A. Constantinides","orcid":"https://orcid.org/0000-0002-0201-310X"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"George A. Constantinides","raw_affiliation_strings":["Imperial College London, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Imperial College London, United Kingdom","institution_ids":["https://openalex.org/I47508984"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5013225839"],"corresponding_institution_ids":["https://openalex.org/I47508984"],"apc_list":null,"apc_paid":null,"fwci":1.0746,"has_fulltext":true,"cited_by_count":9,"citation_normalized_percentile":{"value":0.79798758,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"22","issue":"6","first_page":"1","last_page":"19"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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":0.9998999834060669,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9962000250816345,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9933000206947327,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8760133981704712},{"id":"https://openalex.org/keywords/memory-footprint","display_name":"Memory footprint","score":0.6948866844177246},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5702670812606812},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5085858106613159},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.4777626097202301},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4760194420814514},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.46488329768180847},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4485779404640198},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4399360418319702},{"id":"https://openalex.org/keywords/scratch","display_name":"Scratch","score":0.4198172986507416},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.417266845703125},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.3777921795845032}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8760133981704712},{"id":"https://openalex.org/C74912251","wikidata":"https://www.wikidata.org/wiki/Q6815727","display_name":"Memory footprint","level":2,"score":0.6948866844177246},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5702670812606812},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5085858106613159},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.4777626097202301},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4760194420814514},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.46488329768180847},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4485779404640198},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4399360418319702},{"id":"https://openalex.org/C2781235140","wikidata":"https://www.wikidata.org/wiki/Q275131","display_name":"Scratch","level":2,"score":0.4198172986507416},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.417266845703125},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.3777921795845032},{"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/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","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:10.1145/3626100","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3626100","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3626100","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:10.1145/3626100","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3626100","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3626100","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":[{"score":0.8500000238418579,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[{"id":"https://openalex.org/G2784140359","display_name":"Application Customisation: Enhancing Design Quality and Developer Productivity","funder_award_id":"EP/P010040/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G3496335909","display_name":"Centre for Spatial Computational Learning","funder_award_id":"EP/S030069/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G4587427570","display_name":null,"funder_award_id":"EP/S030069/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G774180880","display_name":null,"funder_award_id":"EP/P010040/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G8719353587","display_name":null,"funder_award_id":"EP/P0","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4387344527.pdf","grobid_xml":"https://content.openalex.org/works/W4387344527.grobid-xml"},"referenced_works_count":37,"referenced_works":["https://openalex.org/W2149381887","https://openalex.org/W2260663238","https://openalex.org/W2338908902","https://openalex.org/W2469490737","https://openalex.org/W2559655401","https://openalex.org/W2566079294","https://openalex.org/W2594653239","https://openalex.org/W2612690371","https://openalex.org/W2789027062","https://openalex.org/W2887447938","https://openalex.org/W2941620283","https://openalex.org/W2944751469","https://openalex.org/W2951829782","https://openalex.org/W2979960955","https://openalex.org/W2982234100","https://openalex.org/W2990138404","https://openalex.org/W2991044292","https://openalex.org/W2999134573","https://openalex.org/W3008515144","https://openalex.org/W3009849929","https://openalex.org/W3093982621","https://openalex.org/W3104151879","https://openalex.org/W3106579642","https://openalex.org/W3176211720","https://openalex.org/W3177491619","https://openalex.org/W4225693694","https://openalex.org/W4241365061","https://openalex.org/W4249502209","https://openalex.org/W4288083474","https://openalex.org/W4288365403","https://openalex.org/W4293261943","https://openalex.org/W4311647561","https://openalex.org/W6703652217","https://openalex.org/W6734558626","https://openalex.org/W6764383489","https://openalex.org/W6768921883","https://openalex.org/W6810536043"],"related_works":["https://openalex.org/W3094340691","https://openalex.org/W3013760193","https://openalex.org/W3162668736","https://openalex.org/W4295943704","https://openalex.org/W4221166601","https://openalex.org/W4366999913","https://openalex.org/W4281678247","https://openalex.org/W3208617247","https://openalex.org/W4381489698","https://openalex.org/W3014007418"],"abstract_inverted_index":{"The":[0],"ever-growing":[1],"computational":[2],"demands":[3],"of":[4,14,53,132,149,165,179],"increasingly":[5],"complex":[6],"machine":[7],"learning":[8,61,90],"models":[9,93,167],"frequently":[10],"necessitate":[11],"the":[12,50,72,130,139,193,207],"use":[13],"powerful":[15],"cloud-based":[16],"infrastructure":[17],"for":[18,30,56,77,215],"their":[19,35,45],"training.":[20],"Binary":[21],"neural":[22,79,102],"networks":[23],"are":[24,82,126],"known":[25],"to":[26,34,85,114,169,199,219],"be":[27,220],"promising":[28],"candidates":[29],"on-device":[31],"inference":[32],"due":[33],"extreme":[36],"compute":[37],"and":[38,191,205,227],"memory":[39,108,146,185,203],"savings":[40,212],"over":[41],"higher-precision":[42],"alternatives.":[43],"However,":[44],"existing":[46],"training":[47,81,104,178],"methods":[48],"require":[49],"concurrent":[51],"storage":[52],"high-precision":[54],"activations":[55,133],"all":[57],"layers,":[58],"generally":[59],"making":[60,88],"on":[62],"memory-constrained":[63],"devices":[64],"infeasible.":[65],"In":[66],"this":[67],"article,":[68],"we":[69,197],"demonstrate":[70,175],"that":[71],"backward":[73],"propagation":[74],"operations":[75],"needed":[76],"binary":[78,101,136],"network":[80,103],"strongly":[83],"robust":[84],"quantization,":[86],"thereby":[87],"on-the-edge":[89],"with":[91],"modern":[92],"a":[94,99,163,183],"practical":[95],"proposition.":[96],"We":[97,173],"introduce":[98],"low-cost":[100],"strategy":[105],"exhibiting":[106],"sizable":[107],"footprint":[109],"reductions":[110,148],"while":[111,151],"inducing":[112],"little":[113],"no":[115],"accuracy":[116,155],"loss":[117],"vs":[118],"Courbariaux":[119],"&amp;":[120],"Bengio\u2019s":[121],"standard":[122],"approach.":[123],"These":[124],"decreases":[125,204],"primarily":[127],"enabled":[128],"through":[129],"retention":[131],"exclusively":[134],"in":[135,159],"format.":[137],"Against":[138],"latter":[140],"algorithm,":[141],"our":[142,201],"drop-in":[143],"replacement":[144],"sees":[145],"requirement":[147],"3\u20135\u00d7,":[150],"reaching":[152],"similar":[153],"test":[154],"(\u00b1":[156],"2":[157],"pp)":[158],"comparable":[160],"time,":[161],"across":[162],"range":[164],"small-scale":[166],"trained":[168],"classify":[170],"popular":[171],"datasets.":[172],"also":[174],"from-scratch":[176],"ImageNet":[177],"binarized":[180],"ResNet-18,":[181],"achieving":[182],"3.78\u00d7":[184],"reduction.":[186],"Our":[187],"work":[188],"is":[189],"open-source,":[190],"includes":[192],"Raspberry":[194],"Pi-targeted":[195],"prototype":[196],"used":[198],"verify":[200],"modeled":[202],"capture":[206],"associated":[208],"energy":[209,225],"drops.":[210],"Such":[211],"will":[213],"allow":[214],"unnecessary":[216],"cloud":[217],"offloading":[218],"avoided,":[221],"reducing":[222],"latency,":[223],"increasing":[224],"efficiency,":[226],"safeguarding":[228],"end-user":[229],"privacy.":[230]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":3}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
