{"id":"https://openalex.org/W4414760848","doi":"https://doi.org/10.1145/3711875.3729145","title":"DAF: An Efficient End-to-End Dynamic Activation Framework for on-Device DNN Training","display_name":"DAF: An Efficient End-to-End Dynamic Activation Framework for on-Device DNN Training","publication_year":2025,"publication_date":"2025-06-23","ids":{"openalex":"https://openalex.org/W4414760848","doi":"https://doi.org/10.1145/3711875.3729145"},"language":"en","primary_location":{"id":"doi:10.1145/3711875.3729145","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3711875.3729145","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3711875.3729145","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 23rd Annual International Conference on Mobile Systems, Applications and Services","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3711875.3729145","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5054692652","display_name":"Renyuan Liu","orcid":"https://orcid.org/0000-0001-9710-6116"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Renyuan Liu","raw_affiliation_strings":["George Mason University, Fairfax, Virginia, USA"],"raw_orcid":"https://orcid.org/0000-0001-9710-6116","affiliations":[{"raw_affiliation_string":"George Mason University, Fairfax, Virginia, USA","institution_ids":["https://openalex.org/I162714631"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048432270","display_name":"Yuyang Leng","orcid":"https://orcid.org/0009-0008-9376-0880"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuyang Leng","raw_affiliation_strings":["George Mason University, Fairfax, Virginia, USA"],"raw_orcid":"https://orcid.org/0009-0008-9376-0880","affiliations":[{"raw_affiliation_string":"George Mason University, Fairfax, Virginia, USA","institution_ids":["https://openalex.org/I162714631"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016488771","display_name":"Kaiyan Liu","orcid":"https://orcid.org/0009-0009-8663-0698"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kaiyan Liu","raw_affiliation_strings":["Geogre Mason University, Fairfax, Virginia, USA"],"raw_orcid":"https://orcid.org/0009-0009-8663-0698","affiliations":[{"raw_affiliation_string":"Geogre Mason University, Fairfax, Virginia, USA","institution_ids":["https://openalex.org/I162714631"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032992976","display_name":"Shaohan Hu","orcid":"https://orcid.org/0000-0002-2877-2665"},"institutions":[{"id":"https://openalex.org/I1305429384","display_name":"JPMorgan Chase & Co (United States)","ror":"https://ror.org/01x3kkr08","country_code":"US","type":"company","lineage":["https://openalex.org/I1305429384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shaohan Hu","raw_affiliation_strings":["JPMorganChase, New York, New York, USA"],"raw_orcid":"https://orcid.org/0000-0002-2877-2665","affiliations":[{"raw_affiliation_string":"JPMorganChase, New York, New York, USA","institution_ids":["https://openalex.org/I1305429384"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034824605","display_name":"Richard Chen","orcid":"https://orcid.org/0000-0002-5912-5620"},"institutions":[{"id":"https://openalex.org/I1305429384","display_name":"JPMorgan Chase & Co (United States)","ror":"https://ror.org/01x3kkr08","country_code":"US","type":"company","lineage":["https://openalex.org/I1305429384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chun-Fu (Richard) Chen","raw_affiliation_strings":["JPMorganChase, New York, New York, USA"],"raw_orcid":"https://orcid.org/0000-0002-5912-5620","affiliations":[{"raw_affiliation_string":"JPMorganChase, New York, New York, USA","institution_ids":["https://openalex.org/I1305429384"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101688277","display_name":"Peijun Zhao","orcid":"https://orcid.org/0000-0003-2843-6941"},"institutions":[{"id":"https://openalex.org/I1305429384","display_name":"JPMorgan Chase & Co (United States)","ror":"https://ror.org/01x3kkr08","country_code":"US","type":"company","lineage":["https://openalex.org/I1305429384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Peijun Zhao","raw_affiliation_strings":["JPMorganChase, New York, New York, USA"],"raw_orcid":"https://orcid.org/0000-0003-2843-6941","affiliations":[{"raw_affiliation_string":"JPMorganChase, New York, New York, USA","institution_ids":["https://openalex.org/I1305429384"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064659321","display_name":"Heechul Yun","orcid":"https://orcid.org/0000-0002-8515-2622"},"institutions":[{"id":"https://openalex.org/I146416000","display_name":"University of Kansas","ror":"https://ror.org/001tmjg57","country_code":"US","type":"education","lineage":["https://openalex.org/I146416000"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Heechul Yun","raw_affiliation_strings":["University of Kansas, Lawrence, Kansas, USA"],"raw_orcid":"https://orcid.org/0000-0002-8515-2622","affiliations":[{"raw_affiliation_string":"University of Kansas, Lawrence, Kansas, USA","institution_ids":["https://openalex.org/I146416000"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102736697","display_name":"Shuochao Yao","orcid":"https://orcid.org/0000-0001-7446-1430"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shuochao Yao","raw_affiliation_strings":["George Mason University, Fairfax, Virginia, USA"],"raw_orcid":"https://orcid.org/0000-0001-7446-1430","affiliations":[{"raw_affiliation_string":"George Mason University, Fairfax, Virginia, USA","institution_ids":["https://openalex.org/I162714631"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.5538,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.88631963,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"196","last_page":"208"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9937000274658203,"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/T10273","display_name":"IoT and Edge/Fog Computing","score":0.9775000214576721,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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":0.5784000158309937},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5444999933242798},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5285000205039978},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.5070000290870667},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.47380000352859497},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.4374000132083893},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.42719998955726624},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.41130000352859497}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7732999920845032},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.5784000158309937},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5577999949455261},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5444999933242798},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5285000205039978},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.5070000290870667},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.47380000352859497},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.4374000132083893},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.42719998955726624},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.41130000352859497},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.36899998784065247},{"id":"https://openalex.org/C176649486","wikidata":"https://www.wikidata.org/wiki/Q2308807","display_name":"Memory management","level":3,"score":0.33399999141693115},{"id":"https://openalex.org/C18131444","wikidata":"https://www.wikidata.org/wiki/Q163585","display_name":"Memory protection","level":5,"score":0.31299999356269836},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.3122999966144562},{"id":"https://openalex.org/C118702147","wikidata":"https://www.wikidata.org/wiki/Q189396","display_name":"Dynamic random-access memory","level":3,"score":0.3102000057697296},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2964000105857849},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.2946999967098236},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.2881999909877777},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.27900001406669617},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.27230000495910645},{"id":"https://openalex.org/C180016635","wikidata":"https://www.wikidata.org/wiki/Q2712821","display_name":"Compression (physics)","level":2,"score":0.2574000060558319},{"id":"https://openalex.org/C13481523","wikidata":"https://www.wikidata.org/wiki/Q412438","display_name":"Image compression","level":4,"score":0.25029999017715454}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3711875.3729145","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3711875.3729145","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3711875.3729145","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 23rd Annual International Conference on Mobile Systems, Applications and Services","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3711875.3729145","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3711875.3729145","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3711875.3729145","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 23rd Annual International Conference on Mobile Systems, Applications and Services","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3013630393","display_name":"Collaborative Research: CPS: Medium: Real-time Criticality-Aware Neural Networks for Mission-critical Cyber-Physical Systems","funder_award_id":"2038658","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5705582075","display_name":"Collaborative Research: CPS: Medium: Real-time Criticality-Aware Neural Networks for Mission-critical Cyber-Physical Systems","funder_award_id":"2038923","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7323781115","display_name":"III: Medium: Collaborative Research: Principled Uncertainty Quantification in Deep Learning Models for Time Series Analysis","funder_award_id":"2107200","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/W4414760848.pdf","grobid_xml":"https://content.openalex.org/works/W4414760848.grobid-xml"},"referenced_works_count":22,"referenced_works":["https://openalex.org/W2082003798","https://openalex.org/W2546571074","https://openalex.org/W2950821050","https://openalex.org/W3035232708","https://openalex.org/W3035718760","https://openalex.org/W4282960063","https://openalex.org/W4283020086","https://openalex.org/W4283766928","https://openalex.org/W4306250089","https://openalex.org/W4380925616","https://openalex.org/W4383753827","https://openalex.org/W4387212477","https://openalex.org/W4387227862","https://openalex.org/W4387968253","https://openalex.org/W4395685900","https://openalex.org/W4399121418","https://openalex.org/W4399320016","https://openalex.org/W4399320034","https://openalex.org/W4399323898","https://openalex.org/W4404034550","https://openalex.org/W4405014122","https://openalex.org/W4405031620"],"related_works":[],"abstract_inverted_index":{"Recent":[0],"advancements":[1],"in":[2],"on-device":[3],"training":[4,34],"for":[5,14,38,54],"deep":[6],"neural":[7],"networks":[8],"have":[9],"underscored":[10],"the":[11,20],"critical":[12],"need":[13],"efficient":[15],"activation":[16,56],"compression":[17],"to":[18],"overcome":[19],"memory":[21,31,60,75],"constraints":[22],"of":[23],"mobile":[24],"and":[25,35,74],"edge":[26],"devices.":[27],"As":[28],"activations":[29],"dominate":[30],"usage":[32],"during":[33],"are":[36],"essential":[37],"gradient":[39],"computation,":[40],"compressing":[41],"them":[42],"without":[43],"compromising":[44],"accuracy":[45],"remains":[46],"a":[47],"key":[48],"research":[49],"challenge.":[50],"While":[51],"existing":[52],"methods":[53],"dynamic":[55],"quantization":[57],"promise":[58],"theoretical":[59],"savings,":[61],"their":[62],"practical":[63],"deployment":[64],"is":[65],"impeded":[66],"by":[67],"system-level":[68],"challenges":[69],"such":[70],"as":[71],"computational":[72],"overhead":[73],"fragmentation.":[76]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-08-06T08:24:18.245995","created_date":"2025-10-10T00:00:00"}
